NYU Data Science newsletter – February 22, 2016

GROUP CURATION: N/A

… There is a good chance your employer and health insurer (both partnered with big government) is currently or soon about to mine data about where and how you shop, where you eat out, whether and when you vote, and the prescription drugs you use – to predict your state of health, forecast future health problems and recommend preventive treatments.

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While this may have some potential positive benefits like decreasing healthcare costs and nudging you to eat better foods, exercise more and use cheap preventive health care services – it is rife with diagnostic accuracy problems at this time considering the high rate of false positives, bad data, patterns that mean nothing, correlations that do not equal causation, and discounting genetic and other factors. Human physiology is a high causal density environment and assessing overall health is tricky even for trained physicians.

A group of scientists from the New York City-based Child Mind Institute, a non-profit that provides treatment and does research, plans to scan the brains of 10,000 New York City children to find the physical markers of a range of psychiatric disorders when they first take root. It’s one of the largest and broadest studies of its kind.

Scientists say that about half of all adult psychiatric disorders begin around the age of 14, and so understanding what brain development looks like when it first gets disrupted will help prevent more serious illness down the line.

The study is expected to cost $30 million and take five to 10 years to complete.

GE has bet big on the Industrial Internet — the convergence of industrial machines, data, and the Internet. The company is putting sensors on gas turbines, jet engines, and other machines; connecting them to the cloud; and analyzing the resulting flow of data. The goal: identify ways to improve machine productivity and reliability. This MIT Sloan Management Review case study looks at how this traditional manufacturer is remaking itself into a modern digital business.

By analyzing data from police departments, a predictive, early warning system can be used to target resources for officers who would most benefit in terms of reducing negative interactions with the public. This system will:

Decrease the probability that an officer has a negative interaction with the public – We can improve over the threshold-based systems currently used in many police departments by identifying and using only the factors that are most predictive of whether an officer will have a negative interaction with a member of the public.

Enable police departments to target limited resources on the officers that most need additional training – Supervisors will be able to use this system to see which officers are most in need of counseling, training, or other assistance to best prepare them to deal safely and positively with individuals in their communities.

… If the 10–15 year pattern repeats itself, the next computing era should enter its growth phase in the next few years. In that scenario, we should already be in the gestation phase. There are a number of important trends in both hardware and software that give us a glimpse into what the next era of computing might be. Here I talk about those trends and then make some suggestions about what the future might look like.

Many of us know the feeling of standing in front of a subway map in a strange city, baffled by the multi-coloured web staring back at us and seemingly unable to plot a route from point A to point B.

Now, a team of physicists and mathematicians has attempted to quantify this confusion and find out whether there is a point at which navigating a route through a complex urban transport system exceeds our cognitive limits.

I just got back from attending a meeting organized by a new group called ASAPbio whose mission is to promote the use of pre-prints in biology. … By the end of the meeting’s 24 hours it seemed like nearly everyone in attendance was sold on the idea that biomedical researchers should all post pre-prints of their work, and had already turned their attention to questions about how to do it. And there was a surprisingly little resistance to the idea that post-publication review of papers initially posted as pre-prints could, at least in principle, fulfill the functions that pre-publication review currently carries out. That’s not to say there weren’t concerns and even some objections – there were, as I will discuss below. But these were all dealt with to varying degrees, and there seemed to be a general attitude these concerns can be addressed, and did not constitute reasons not to proceed.

For all the huge numbers the Seattle e-commerce giant sports, one that jumps out is the number of employees — 230,800 at the end of 2015. It speaks to how the company has become an employment powerhouse with wide-ranging economic impact.

Blood count. Biopsy. Drug cocktails. Snippets like these tell the story of a person’s experience of cancer. Gather up the stories of hundreds of thousands of people and you could learn about the disease itself.

A team at Memorial Sloan Kettering Cancer Center in New York is training an artificial intelligence to find similarities between cases that human doctors might miss. The software combs through 100 million sentences taken from clinical notes about people with cancer.

On Thursday, a Norcross, GA-based developer came to New York to kick off a hackathon that looks to inspire new ideas and uses for its geospatial mapping platform.

Hexagon Geospatial’s Smart M.Apps is a cloud-based platform that visualizes data in real time on digital maps, such as displaying reported crime patterns or transportation in a city. The company says Smart M.Apps could also be used to predict future activity based on the data it crunches.

Participants in the IGNITE hackathon have a shot at winning up to $100,000 for the grand prize, with a total of $260,000 expected to be disbursed amongst the finalists.

Bioinformatics.org has announced the nominees for the 2016 Benjamin Franklin Award. Voting is open now to Bioinformatics.org members. The winner will be announced at the 2016 Bio-IT World Conference & Expo.

The Benjamin Franklin Award is a humanitarian/bioethics award presented annually by Bioinformatis.org to an individual who has, in his or her practice, promoted free and open access to the materials and methods used in the life sciences. This year’s finalists include the founder of the Encyclopedia of Life; the founder of BioRuby; the past president of the International Society for Computational Biology; and leader of the Human Metabolome Project.

Over the last five years, the rapid growth of Python’s open source data tools have made it a tool of choice for a wide variety of data engineering and data science needs. Hugely successful projects that we now take for granted, such as Jupyter, Pandas, and scikit-learn, were comparatively nascent efforts only a few years ago. Today, data teams worldwide love Python for its accessibility, developer productivity, robust community, and “batteries-included” open source libraries.

During the same time period, the Apache Hadoop ecosystem has risen to the challenge of collecting, storing, and analyzing accelerating volumes of data with the robustness, security, and scalable performance demanded by the world’s largest enterprises.

While the Python and Hadoop ecosystems have each flourished in their own right, they have struggled to work well together due to both high-level architectural and low-level technological challenges.