Opportunities in Agriculture

Why B.Sc. Agriculture?

Approximately 65 percent of the population is dependent on agriculture in India for their livelihood.  India’s varying climatic condition highly supports the diversification of crops and their varietal development. The modern agriculture sector proves helpful in generating human resource to support other sectors within imparting knowledge, linking farmers with researchers and also extending extension services in the overall development of the national economy.

As saturation comes in the most sought for courses like engineering and medical fields, B.Sc. in agriculture offers a silver lining for the admission seekers. Careers in agriculture safeguard the idea of standing away from the general crowd. The course curricula of B.Sc.(Hons.)Agriculture program emphasizes all core areas of agriculture embedded with agriculture heritage of India. This program is the first step in the ladder towards modern agriculture by adopting improved technologies and practices including the most talked off organic farming. The study of modern agriculture leads to better farm yields along with much needed environmental protection and sustainable growth. Keeping in pace with recent advances in different areas of agriculture, the objectives of B.Sc. (Hons.) Agriculture is to nurture young scholars, tap their potentials and groom them to become valuable contributors to the much needed second Green Revolution.

Through passion and perseverance, students can explore how things work and how impossibilities can be turned into realities by studying agriculture. The vast curriculum of B.Sc. Agriculture is highly enriched with various courses like agronomy, soil science, entomology, horticulture, plant physiology, agricultural engineering, agricultural economics, applications of biotechnology, post-harvest management, etc. The syllabi recommended by the ICAR provide detailed knowledge of various streams under agriculture & allied fields and allows the student to choose his/her area of interest for establishing their career. During the four years, they are exposed to different teaching methodologies including refining their communication and expression skills.

What is learnt in 4-year degree of B.Sc. Agriculture?

The agriculture course provides theoretical as well as practical knowledge of the progressive aspects of modern agriculture along with addressing sustainability, which is a must in the current fragile ecosystem.

Besides building expertise through well planned on-field implementation and testing of basic concepts in better production with higher yields resistant to various diseases and value addition of food and flora it also prepares the students in marketing skills of agriculture products, which is need of the hour in the plethora of unemployment.

The learning outcome of various components is:

  • RAWE (Rural Agricultural Work Experience): Under this programme, the students are exposed to real life rural settings with the aim to develop a sense of awareness so that the students can understand the day to day problems of farmers and rural folks. Budding graduates acquire relevant practical experience required for efficient working in agricultural and allied fields wherein they can gauge the difference between what is taught and what is applicable in the field.
  • Experimental Learning–   Under this component, the students undergo training in different organizations and NGOs and attend Industry Interaction Programs, Seminars and Workshops etc. These events offer the students an opportunity to observe and assimilate the structure, the organizational traits and the business environment of the industry and develop communication skills, analytical abilities and gain awareness regarding the prerequisites of job requirements in all sectors.
  • Educational Visits – It includes regular visits to different KVKs (Krishi Vigyan Kendra), major agricultural institutes and research centres to understand the basic framework of research and gaining practical knowledge.
  • Agri-business: Entrepreneurial ventures in agriculture are the utmost need of the hour to support the farming industry as well as the economy by developing agri-entrepreneurial skills in students.

Besides above mentioned components, education in agriculture unlocks the mysteries and struggles to solve problems related to abiotic and biotic stress in crops which result into crop loss and lower productivity  by combining the expertise with help of major components like agronomy, horticulture,  weed sciences, plant pathology, plant breeding, soil science, genetic engineering, agricultural entomology, agricultural economics, etc. in order to protect the crops ensuring food security and sustainable agriculture.

Therefore, the course provides crucial information about the various projects developed after independence and their major role in improving the farming lot and economy of our country.  The student also receives knowledge of social forestry tree species used in agriculture, their role and importance in sustaining food chain, food web and biodiversity.

The course inculcates an overall understanding and bearing importance of the impact of globalization and diversity in modern agriculture organizations and prepares the students in critical thinking, analysis and problem-solving. It develops an understanding of current events and present issues in agriculture and their bearing in future agriculture. Students precisely learn to examine the relationships between inputs and outputs to boost profitability. They will understand the employer’s characteristics and decision-making, which in turn will enhance the success of any agricultural enterprise.

Career opportunities after completion of Bachelor of Agriculture

With the application of advanced agricultural technologies in the modern world, there’s a lot of scope in bringing out new horizons towards increasing standards of agriculture.

Therefore, for agriculture graduates, major domains within the ambit of the agricultural sector include:

  • Higher education and research fields in public and private institutions.
  • The State Department of Agriculture and Horticulture as Agricultural Development Officers (ADOs) and Horticulture Development Officers (HDOs), respectively.
  • In public and private sector banks as Rural Development Officers (RDOs).
  • Soil Conservation and Soil Testing Division, Department of Agriculture as Trainee Officers
  • Various fertilizer organizations as Technical Personnel
  • The graduates can also find various options in pesticides and seed companies, starting from Management Trainee to Marketing Officer in Marketing Division; Research Officers in Research & Development Division, etc.
  • They can also find employability as Technical Personnel in various food and seed processing industries.
  • In sugar industries in various capacities.
  • Can adopt agri business as a profession.
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Horticulture- A Nutritive Future

The horticulture sector encompasses a wide range of crop cultivation such as fruits, vegetables, ornamentals, flowers, spices, plantations, medicinal and aromatic plants.  India, with its wide variability of climate and soil, is highly favourable for growing a large variety of horticultural crops. It is the fastest growing sector within agriculture.  After the Green Revolution in mid-sixties, it became clear that horticulture is the best option to increase agriculture growth rate. The horticultural production has surpassed the production statistics of field crops. On the global map, India is one of the leading exporters of fruits & vegetables with an export of approximate INR 38.56 billion, comprising of INR 26.35 billion worth of fruits & INR 12.21 billion of vegetables. The nation is the largest producer of okra amongst vegetables & ranks second in production of potatoes (10%), onions, cauliflowers, brinjal, cabbages, etc. It is also the largest producer & consumer of cashew nuts and is the third largest producer of coconut and leads 90 coconut-producing countries of the world.

The most significant development that happened in the last decade is that horticulture has moved from rural confines to commercial production and this changing scenario has encouraged private sector investment in production system management. The recent years have seen technological infusions like micro-irrigation, precision farming, greenhouse cultivation and improved post-harvest management impacting the development.

Many national and international organizations are playing important role in promoting the latest technologies and are researching on emerging problems of farmers.

In this view, at SGT University we prepare our students to get familiarize about these problems and their effective solutions. Recently, the students attended an International Conference on Horticulture & Horti Expo 2018 at IARI Mela ground, New Delhi from 25 to 27 October 2018 organized by Indian Council of Food and Agriculture (ICFA). This is one of the ways to understand the present scenario in horticulture which helps to develop problem-solving skills. Horticulture is the future of agriculture in the global market. Lots of opportunities are waiting for budding agriculturists in this sector.

-Dr. Vinita Rajput
Assistant Professor- Horticulture

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In The Battle To Control Drug Costs, Old Patent Laws Get New Life

In the drug pricing battle, progressive lawmakers such as Sen. Bernie Sanders (I-Vt.) and patients’ rights activists rarely find themselves in step with the health industry’s big players.

But in a twist, these usually at-odds actors are championing similar tactics to tame prescription drug prices.

The strategies involve repurposing two obscure and rarely deployed workarounds in patent law that, in different ways, empower the federal government to take back patents and license them to other companies. The first is known as “march-in rights.” The second is generally referred to as Section 1498 because of its location in the U.S. Code.

Sanders has in recent years pointed to these steps as useful tools in the drug-pricing debate.

As an indicator of how high the stakes have become, these ideas also are finding traction among some major health industry players — most notably, two large trade groups that represent health plans and the “middlemen” companies that negotiate drug coverage.

“It used to be the case that everyone played nicely with one another, and now as prices have gone up, the knives have come out,” said Jacob Sherkow, a law professor at New York University who focuses on intellectual property and the pharmaceutical industry.

The push for march-in rights gained momentum this past summer, when activists launched a campaign challenging the patent for Truvada, the HIV treatment by Gilead Sciences that has been shown to reduce the risks of contracting HIV when taken daily as a preventive.

Initially, patient advocates focused mainly on shaming insurance companies into providing better coverage of that pill, also known as pre-exposure prophylaxis, or PrEP, because it is taken before someone is exposed to the virus. But they soon found themselves targeting a frustration that insurance happened to share: the drug’s list price.

James Krellenstein, co-founder of the PrEP4All Collaboration, an advocacy group, was part of that campaign. Health plans had put barriers in place to limit access to the drug, he said. But they, too, were worried about Truvada’s escalating price.

“You can’t scale up to a level you need to unless we deal with the pricing problem,” he said.

Now, as insurers signal they might adopt an approach similar to that of the campaign, he voiced skepticism. On the one hand, the support could benefit their cause. At the same time, “they have their interests, and that’s not the interests of public health,” Krellenstein said.

Still, in Washington, the influence of groups like America’s Health Insurance Plans (AHIP), which is the largest trade association for health insurers, and the Pharmaceutical Care Management Association (PCMA), which represents those middlemen companies known as pharmacy benefit managers (PBMs), could add political credibility to these long-shot ideas.

President Donald Trump has said curbing prescription drug costs is a high priority. But, as congressional action seems increasingly unlikely, these two approaches offer another possible path forward.

They are “already part of a law that is intact. … An option the administration can take now,” said Walid Gellad, director of the Center for Pharmaceutical Policy and Prescribing at the University of Pittsburgh.

AHIP says the Department of Health and Human Services should lean on a federal statute that lets the government take over drug patents and grant them to other manufacturers, as long as it adequately compensates the original patent holder.

Meanwhile, PCMA is pressing the administration to use the “march-in rights” championed by HIV activists. Provided under the 1980 Bayh-Dole Act, they empower the government to rescind a drug’s patent and let other companies develop versions of it. This applies only if government funding helped develop a drug, and it can be invoked only in specific circumstances, including a threat to public health or safety.

“Everybody is feeling the heat, and I think that is the reason you’re seeing this interest in using the tools that exist,” said Amy Kapczynski, professor at Yale Law School who has written extensively about drug patents.

But opposition is strong among drugmakers.

“Policies should spur competition and new innovations to meet patient needs, not disincentivize them such as the use of 1498 and march-in could do,” said Priscilla VanDerVeer, a spokeswoman for the Pharmaceutical Researchers and Manufacturers of America, or PhRMA, a trade and lobbying group.

Gilead, which manufactures Truvada, has a similar stance.

“We believe that there is no rationale or precedent for the government to exercise march-in or other [intellectual property] rights related to Truvada for PrEP,” said Ryan McKeel, a spokesman for Gilead. The company’s other efforts to make the drug “available for health and safety needs,” he added, “clearly satisfy” the company’s legal requirements.

And the potential for march-in authority is still theoretical. It has never been used, despite at least five petitions to the National Institutes of Health, three of which cited high drug prices.

Section 1498 was used to negotiate lower drug prices in the 1960s and ’70s, but has since faded. In 2001, during the nation’s anthrax scare, the Department of Health and Human Services threatened to invoke it to procure more of the antibiotic used to treat the deadly bacterial disease, according to contemporaneous reports. Last year, Louisiana’s health secretary unsuccessfully tried to use it to ease the toll pricey hepatitis C medications exerted on the state’s Medicaid program.

NIH Director Francis Collins remains skeptical, repeatedly saying that a drug’s price doesn’t constitute a health or safety concern within the agency’s jurisdiction.

HHS Secretary Alex Azar, speaking at a June Senate hearing, described march-in, also known as “compulsory licensing,” as a “socialist” approach.

But health pans and other payers, increasingly squeezed by fast-climbing prices, are undeterred — touting this kind of intervention as a “market-based solution.”

“The trends of drug prices in this country suggest that we all collectively need to find new approaches — including new approaches that are available under existing law — to try to change this trend,” said Mark Hamelburg, AHIP’s senior vice president of federal programs.

Kaiser Permanente, the health system and insurance provider, called for leveraging Section 1498 in a public comment submitted to HHS about its strategy to bring down drug prices. In a similar filing, Humana, a major insurer, pointed to “existing law [that] allows for actions around patents,” singling out march-in rights.

Humana did not respond to requests for comment. Both PCMA and Kaiser Permanente declined to comment beyond their statements. (Kaiser Health News is not affiliated with Kaiser Permanente.)

Nonetheless, experts say there are serious sticking points.

Neither of these legal provisions would be a sweeping solution. And both require administration buy-in.

“They’re only as effective as the government’s willingness to pursue them,” said Robin Feldman, a law professor at the University of California-Hastings.

Simply taking a patent doesn’t bring down prices, either. There are other ways manufacturers gain favorable market positioning for specific drugs, said Rachel Sachs, an associate law professor at Washington University in St. Louis who tracks drug-pricing laws.

And creating an opening for generics is only one step. Another drugmaker would still need to create a competing product, gain approval and make it available. Then, theoretically, market competition can kick in.

Finally, there’s no guarantee such savings would benefit consumers, argued Nicholson Price, an assistant professor at the University of Michigan Law School. Insurance plans or PBMs could simply bargain greater discounts on drugs and pocket the money. (AHIP says any savings should be passed on.)

That’s the fundamental question, Krellenstein said.

“Is this going to be more armor in the fighting [between payers and drug companies]?” he said. “Or is it actually going to be a dramatic reform that actually results in real changes, that actually makes it easier for Americans to access the medications they need?”

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of the Kaiser Family Foundation, which is not affiliated with Kaiser Permanente.

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The informal water markets of Bangalore are a view of the future

Bangalore is home to some ten million people. It might also be the next city to experience “day zero”: when it runs out of groundwater entirely.

But in settlements just outside the city centre, people already live without municipal water supplies. Our research found that families – largely women – must piece together drinking, cooking and washing water through a mixture of limited tap supply, communally bought canned water, and “water ATMs”.

It takes enormous time, energy and money to negotiate these water markets. Bangalore offers a glimpse of a possible future, as more cities around the world approach “day zero”.

Beyond municipal water
In settlements just outside the city centre, the reach of the official water board is limited. These areas are not serviced by the municipality’s supply of Kaveri River water. Low-income households, especially migrants, living in these neighbourhoods have to negotiate limited water sources that are available in a narrow window of time.

The Bangalore water board does supply a range of tanker water services. However, tanker water is typically used for washing, cleaning, and other household purposes, but not for cooking and drinking. Residents feel that this tanker water is “dirty” and complain that it causes sore throats and gastrointestinal problems when consumed directly.

To access drinkable water, some of the more fortunate areas have access to pipe connections where water flows once a week for an hour or so. However, the borewells connected to these pipes are continually at risk of being depleted.

The “lineman” of a given neighbourhood is the one who decides which area will get water from these pipes, and at what hours. However, such decisions are limited by the availability of groundwater, which has to remain untouched periodically to create sufficient “recharge” of groundwater for adequate discharge. This limited supply forces the households to look for elsewhere for drinking and cooking water.

Some places have access to water kiosks or water “ATMs”. These water kiosks are also connected to groundwater sources and water filters. A household pays 5 Indian rupees (INR) for 20 litres of water.

If kiosk water is limited or absent, residents have to depend on “canned” water for drinking and cooking purposes. One such plastic can of 20 litres costs between 25 to 35 INR depending on locality and frequency of purchase.

The more reputable brands cost as much as 70 INR, which is far beyond the reach of the poor. An average household of five members needs about three to five cans a week.

If a “can” delivery service refuses to deliver to households in one of these remote neighbourhoods, entrepreneurs arise to fill in the supply gap. Geetamma*, who runs a small eatery in one such neighbourhood, buys 20-litre cans in bulk and resells these to households with a small profit margin of 2 INR per can.

When municipally supplied or purchased tanker water is insufficient, households purchase water from private tankers. It is priced at 300-500 INR per tanker for 4,000-5,000 litres. Households collect the water in underground concrete tanks or in 200-litre plastic drums. In some neighbourhoods, residents collectively buy tanker water by pooling resources. The poorest migrants often resort to the collective option, or even to buy in smaller per-bucket quantities of 15 litres for 2 INR.

The range of ways that people access to water in peri-urban Bangalore demonstrates that some transactions are formal, some are informal, and that others are a peculiar combination of both.

A huge cost
To secure water supplies from all these varied sources, people must spend a huge proportion of their income. A back-of-the-envelope calculation suggests that the monthly spend on water for a low-income household is between 5-8% of total income. Despite this relatively high rate of expenditure, such households are still far below the minimum target supply of 70 litres per person per day.

This limited water supply also comes at the cost of time. Based on our sampling of experiences in seven neighbourhoods of southeast Bangalore, adult women such as Manjula* typically spend between 3 and 5 hours a week working to secure water supplies – time that could be used to supplement household income.

The water markets in Bangalore rely heavily on interpersonal relationships and collective action. These communities have so far been resilient and resourceful, but the formal and informal systems are in a delicate balance. One big supply-side shock can at any time distort this equilibrium.

Courtesy: The Conversation.

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The Training Of Dr. Robot: Data Wave Hits Medical Care

The technology used by Facebook, Google and Amazon to turn spoken language into text, recognize faces and target advertising could help doctors combat one of the deadliest killers in American hospitals.

Clostridium difficile, a deadly bacterium spread by physical contact with objects or infected people, thrives in hospitals, causing 453,000 cases a year and 29,000 deaths in the United States, according to a 2015 study in the New England Journal of Medicine. Traditional methods such as monitoring hygiene and warning signs often fail to stop the disease.

But what if it were possible to systematically target those most vulnerable to C-diff? Erica Shenoy, an infectious-disease specialist at Massachusetts General Hospital, and Jenna Wiens, a computer scientist and assistant professor of engineering at the University of Michigan, did just that when they created an algorithm to predict a patient’s risk of developing a C-diff infection, or CDI. Using patients’ vital signs and other health records, this method — still in an experimental phase — is something both researchers want to see integrated into hospital routines.

The CDI algorithm — based on a form of artificial intelligence called machine learning — is at the leading edge of a technological wave starting to hit the U.S. health care industry. After years of experimentation, machine learning’s predictive powers are well-established, and it is poised to move from labs to broad real-world applications, said Zeeshan Syed, who directs Stanford University’s Clinical Inference and Algorithms Program.

“The implications of machine learning are profound,” Syed said. “Yet it also promises to be an unpredictable, disruptive force — likely to alter the way medical decisions are made and put some people out of work.

Machine learning (ML) relies on artificial neural networks that roughly mimic the way animal brains learn.

As a fox maps new terrain, for instance, responding to smells, sights and noises, it continually adapts and refines its behavior to maximize the odds of finding its next meal. Neural networks map virtual terrains of ones and zeroes. A machine learning algorithm programmed to identify images of coffee cups might compare photos of random objects against a database of coffee cup pictures; by examining more images, it systematically learns the features to make a positive ID more quickly and accurately.

Shenoy and Wiens’ CDI algorithm analyzed a data set from 374,000 inpatient admissions to Massachusetts General Hospital and the University of Michigan Health System, seeking connections between cases of CDI and the circumstances behind them.

The records contained over 4,000 distinct variables. “We have data pertaining to everything from lab results to what bed they are in, to who is in the bed next to them and whether they are infected. We included all medications, labs and diagnoses. And we extracted this on a daily basis,” Wiens said. “You can imagine, as the patient moves around the hospital, risk evolves over time, and we wanted to capture that.”

As it repeatedly analyzes this data, the ML process extracts warning signs of disease that doctors may miss — constellations of symptoms, circumstances and details of medical history most likely to result in infection at any point in the hospital stay.

Such algorithms, now commonplace in internet commerce, finance and self-driving cars, are relatively untested in medicine and health care. In the U.S., the transition from written to electronic health records has been slow, and the format and quality of the data still vary by health system — and sometimes down to the medical practice level — creating obstacles for computer scientists.

But other trends are proving inexorable: Computing power has grown exponentially while getting cheaper. Once, creating a machine learning algorithm required networks of mainframe computers; now it can be done on a laptop.

Radiology and pathology will experience the changes first, experts say. Machine learning programs will most easily handle analyzing images. X-rays and MRI, PET and CT scans are, after all, masses of data. By crunching the data contained in thousands of existing scan images along with the diagnoses doctors have made from them, algorithms can distill the collective knowledge of the medical establishment in days or hours. This enables them to duplicate or surpass the accuracy of any single doctor.

Machine learning algorithms can now reliably diagnose skin cancers (from photographs) and lung cancer, and predict the risk of seizures.

Google research scientist Lily Peng, a physician, led a team that developed a machine learning algorithm to diagnose a patient’s risk of diabetic retinopathy from a retinal scan. DR, a common side effect of diabetes, can lead to blindness if left untreated. The worldwide rise in diabetes rates has turned DR into a global health problem, with the number of cases expected to rise from 126.6 million in 2011 to 191 million by 2030 — an increase of nearly 51 percent. Its presence is indicated by increasingly muddy-looking scan images.

Peng’s team gathered 128,000 retinal scans from hospitals in India and the U.S. and assembled a team of 54 ophthalmologists to grade them on a 5-point scale for signs of the disease. Multiple doctors reviewed each image to average out individual differences of interpretation.

Once “trained” on an initial data set with the diagnoses, the algorithm was tested on another set of data — and there it slightly exceeded the collective performance of the ophthalmologists.

Now Peng is working on applying this tool in India, where a chronic shortage of ophthalmologists means DR often goes undiagnosed and untreated until it’s too late to save a patient’s vision. (This is also a problem in the U.S., where 38 percent of adult diabetes patients do not get the recommended annual eye check for the disease, according to the Centers for Disease Control.)

A group of Indian hospitals is now testing the algorithm. Ordinarily, a scan is done, and a patient may wait days for results after a specialist — if available — reads the image. The algorithm, via software running on hospital computers, makes the results available immediately and a patient can be referred to treatment.

Last year, the Food and Drug Administration approved the first medical machine learning algorithm for commercial use by the San Francisco company Arterys. Its algorithm, “DeepVentricle,” performs in 30 seconds a task doctors typically do by hand — drawing the contours of ventricles from multiple MRI scans of the heart muscle in motion, in order to calculate the volume of blood passing through. That takes an average of 45 minutes. “It’s automating something that is important — and tedious,” said Carla Leibowitz, Arterys’ head of strategy and marketing.

If adopted on a broad scale, such technologies could save lots of time and money. But such change is disruptive.

“The fact that we have identified potential ways to gut out costs is good news. The problem is the people who get gutted are not going to like it — so there will be resistance,” said Eric Topol, director of the Scripps Translational Science Institute. “It undercuts how radiologists do their work. Their primary work is reading scans — what happens when they don’t have to do that?”

The shift may not put a lot of doctors out of work, said Topol, who co-authored a piece in JAMA exploring the issue. Rather, it will likely push them to find new ways to apply their expertise. They may focus on more challenging diagnoses where algorithms continue to fall short, for instance, or interact more with patients.

Beyond this frontier, algorithms can provide a more precise prognosis for the course of a disease — potentially reshaping treatment of progressive ailments or addressing the uncertainties in end-of-life care. They can anticipate fast-moving infections like CDI and chronic ailments such as heart failure.

As the U.S. population ages, heart failure will be a rising burden on the health system and on families.

“It’s the most expensive single disease as a category because of the extreme disability it causes and the high demand for care it imposes, if not managed really tightly,” said Walter “Buzz“ Stewart, vice president and chief research officer at Sutter Health, a health system in Northern California. “If we could predict who was going to get it, perhaps we could begin to intervene much earlier, maybe a year or two years earlier than when it usually happens — when we admit a patient to the hospital after a cardiac event or crash.”

Stewart has collaborated on several studies aiming to address that problem. One, done with Georgia Tech computer scientist Jimeng Sun, predicts whether a patient will develop heart failure within six months, based on 12 to 18 months of outpatient medical records.

These tools, Stewart said, are leading to the “mass customization of health care.” Once algorithms can anticipate incipient stages of conditions like heart failure, doctors will be better able to offer treatments tailored to the patient’s circumstances.

Despite its scientific promise, machine learning in medicine remains terra incognita in many ways. It adds a new voice — the voice of the machine — to key medical decisions, for instance. Doctors and patients may be slow to accept that. Adding to potential doubts, machine learning is often a black box: Data go in, and answers come out, but it’s often unclear why certain patterns in a patient’s data point, say, to an emerging disease. Even the scientists who program neural networks often don’t understand how they reach their conclusions.

“It’s going to make a big difference in how decisions are made — things will become much more data-driven than they used to be,” said John Guttag, a professor of computer science at MIT. Doctors will rely on these increasingly complex tools to make decisions, he said, and “have no idea how they work.” And, in some cases, it will be hard to figure out why bad advice was given.

And while health data are proliferating, the quantity, quality and format vary by institution, and that affects what the algorithms “learn.”

“That is a huge issue with modeling and electronic health records,” Sun said. “Because the data are not curated for research purposes. They are collected as a byproduct of care in day-to-day operations, and utilized mainly for billing and reimbursement purposes. The data is very, very noisy.”

This also means that data may be inconsistent, even in an individual patient’s records. More important, one size does not fit all: An algorithm developed with data from one hospital or health system may not work well for another. “So you need models for different institutions, and the models become quite fragile, you might put it,” Sun said. He is working on a National Institutes of Health grant studying how to develop algorithms that will work across institutions.

And the tide of available medical data continues to rise, tantalizing scientists. “Think about all the data we are collecting right now,” Wiens said. “Electronic health records. Hospitalizations. At outpatient centers. At home. We are starting to collect lots of data on personal monitors. These data are valuable in ways we can’t yet know.”

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of the Kaiser Family Foundation, which is not affiliated with Kaiser Permanente.

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Tuition-Free Med School Touches Off Multimillion-Dollar Debate

New York University’s School of Medicine is learning that no good deed goes unpunished.

The highly ranked medical school announced with much fanfare Aug. 16 that it is raising $600 million from private donors to eliminate tuition for all its students — even providing refunds to those currently enrolled. Before the announcement, annual tuition was $55,018.

NYU leaders said the move will help address the increasing problem of student debt among young doctors, which many educators argue pushes students to enter higher-paying specialties instead of primary care, or deters them from becoming doctors in the first place.

“A population as diverse as ours is best served by doctors from all walks of life, we believe, and aspiring physicians and surgeons should not be prevented from pursuing a career in medicine because of the prospect of overwhelming financial debt,” Dr. Robert Grossman, the dean of the medical school and CEO of NYU Langone Health, said in a statement. NYU declined a request to elaborate further on its plans.

The announcement generated headlines and cheers from students. But not everyone thinks that making medical school tuition-free for all students, including those who can afford it, is the best way to approach the complicated issue of student debt.

“As I start rank ordering the various charities I want to give to, the people who can pay for medical school in cash aren’t at the top of my list,” said Craig Garthwaite, a health economist at Northwestern University’s Kellogg School of Management.

“If you had to find some cause to put tons of money behind, this strikes me as an odd one,” said Dr. Aaron Carroll, a pediatrician and researcher at Indiana University.

Still, medical education debt is a big issue in health care. According to the Association of American Medical Colleges, which represents U.S. medical schools and academic health centers, 75 percent of graduating physicians had student loan debt as they launched their careers, with a median tally of $192,000 in 2017. Nearly half owed more than $200,000.

But it is less clear how much of an impact that debt has on students’ choice of medical specialty. The AAMC’s data suggests debt does not play as big a role in specialty selection as some analysts claim.

If debt were a huge factor, one would expect that doctors who owed the most would choose the highest-paying specialties. But that’s not the case.

“Debt doesn’t vary much across the specialties,” said Julie Fresne, AAMC’s director of student financial services and debt management.

Garthwaite agrees. He said surveys in which young doctors claim debt as a reason for choosing a more lucrative specialty should be viewed with suspicion. “No one [who chooses a higher-paying job] says they did it because they want two Teslas,” he said. “They say they have all this debt.”

Carroll questioned how much difference even $200,000 in student debt makes to people who, at the lowest end of the medical spectrum, still stand to make six figures a year. “Doctors in general do just fine,” he said. “The idea we should pity physicians or worry about them strikes me as odd.”

Choice of specialty is also influenced by more than money. Some specialties may bring less demanding lifestyles than primary care or more prestige. Carroll said his surgeon father was not impressed when he opted for pediatrics, calling it a “garbageman” specialty.

There is also an array of government programs that help students afford medical school or forgive their loans, although usually in exchange for agreeing to serve for several years either in the military or in a medically underserved location. The federal National Health Service Corps, for example, provides scholarships and loan repayments to medical professionals who agree to work in mostly rural or inner-city areas with a shortage of medical professionals. And the Department of Education oversees the Public Service Loan Forgiveness program, which cancels outstanding loan balances after 10 years for those who work for nonprofit employers.

Medical schools themselves are addressing the student debt problem. Many — including NYU — have created programs that let students finish medical school in three years rather than four, which reduces the cost by 25 percent. And the Cleveland Clinic, together with Case Western Reserve University, has a tuition-free medical school aimed at training future medical researchers that takes five years but grants graduates who hold both a doctor of medicine title and a special research credential or master’s degree.

This latest move by NYU, however, is part of a continuing race among top-tier medical schools to attract the best students — and possibly improve their national rankings.

In 2014, UCLA announced it would provide merit-based scholarships covering the entire cost of medical education (including not just tuition, like NYU, but also living expenses) to 20 percent of its students. Columbia University announced a similar plan earlier this year, although unlike NYU and UCLA, Columbia’s program is based on students’ financial need.

The programs are funded, in whole or in part, by large donors whose names brand each medical school — entertainment mogul David Geffen at UCLA, former Merck CEO P. Roy Vagelos at Columbia, and Home Depot co-founder Kenneth Langone at NYU.

Economist Garthwaite said it is all well and good if top medical schools want to compete for top students by offering discounts. But if their goal is to encourage more students to enter primary care or to steer more people from lower-income families into medicine, giving free tuition to all “is not the most target-efficient way to reach that goal.”

Kaiser Health News is a nonprofit news service covering health issues. It is an editorially independent program of the Kaiser Family Foundation, which is not affiliated with Kaiser Permanente.

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Hydrogen – Coal of the future (#2)

Why is the idea of a hydrogen economy so popular? What are the steps to getting there?

One of the main motivations is that scientists, engineers, and politicians see the great promise of hydrogen as a clean fuel, no pollution. That’s the nirvana that everyone’s looking for. Politically, it’s very attractive. A lot of areas in the country have real air quality problems. Something has to be done. Hydrogen may be a solution. It’s just going to take a while. There’s a legitimate case for research and development. There could be a dramatic breakthrough in fuel cell operation. There have already been significant reductions in the fuel cell operating costs because material scientists have been able to reduce the amount of platinum used in fuel cell catalysts.

Hydrogen – Coal of The Future (#2)
– Rajneesh Wadhwa

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Hydrogen – Coal of The Future (#1)

If I were a science-fiction writer trying to dream up the perfect fuel, I could hardly do better than hydrogen. High in energy, it produces almost no pollution when burned. It’s also the simplest and most abundant of elements, making up 90 percent of all matter. It’s present in stars and living things, in fossil fuels and, most mesmerizingly of all, in water.

A transition to a hydrogen economy is, at best, decades away. We have a long way to go. Gas is cheap. How can hydrogen compete? If we believe that the corrective policy is to put a tax on gasoline, given the social cost of oil is $50 a barrel, say, you divide that by 42 gallons in a barrel, that’s more than a $1 tax per gallon of gasoline. Which politician would be willing to put a tax of a dollar on gasoline? So that’s the essence of the problem. We’re not paying the true cost of gasoline. The point is that hydrogen and alternative fuels have to compete in that type of market.

Hydrogen – Coal of The Future (#1)
– Rajneesh Wadhwa

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