Using big data to manage medical expectations — Cynthia Rudin

MIT Sloan Asst. Prof. Cynthia Rudin

From The Health Care Blog 

For all the advances in both medicine and technology, patients still face a bewildering array of advice and information when trying to weigh the possible consequences of certain medical treatments. But a hands-on, data-driven tool I have developed with some colleagues can now help patients obtain personalized predictions for their recovery from surgery. This tool can help patients better manage their expectations about their speed of recovery and long-term effects of the procedure.

People need to be able to fully understand the possible effects of a medical procedure in a realistic and clear way. Seeking to develop a model for recovery curves, we developed a Bayesian modeling approach to recovery curve prediction in order to forecast sexual function levels after prostatectomy, based on the experiences of 300 UCLA clinic patients both before radical prostatectomy surgery and during the four years immediately following surgery. The resulting interactive tool is designed to be used before the patient has a prostatectomy in order to help the patient manage expectations. A central predicted recovery curve shows the patient’s average sexual function over time after the surgery. The tool also displays a range of lighter-colored curves illustrating the broader range of possible outcomes.

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Maybe the search for the Malaysian Airlines plane needed a chief data officer — Stuart Madnick

MIT Sloan Professor Stuart Madnick

MIT Sloan Professor Stuart Madnick

From Quartz

The search for an airplane lost on a 2,500-mile international journey requires consolidating information from many organizations, both public and private, from all over the world. It involves analyzing vast amounts of radar, sonar, and satellite data, coming from many diverse sources, including military bases, air traffic controllers, naval ships, and other airplanes.

What if the authorities investigating the missing plane had been prepared to manage big data the way many corporations do? What if the investigation had an executive level position responsible for collecting and analyzing all of the dispersed and diverse data that were available and potentially relevant to the search? What if a multinational chief data officer (CDO) had been in place to manage all of the information that was available?

Companies have recognized the value of just such a position for some time. The first reported chief data officer was established in 2003 by Capital One Financial Corp., Yahoo, and Microsoft Germany were early adopters. In little over a decade, hundreds of organizations, including US federal and state agencies, have created chief data officer positions, although the jobs often are given different titles. In time, the initials CDO may become as familiar as CEO, CFO, and CIO.

Driving the trend is the phenomenon of big data—the explosion of information made possible by the great advances that we have seen in recent years in communications, computers, and storage.

Read the full post at Quartz.

Stuart Madnick is co-head of the MIT Total Data Quality Management and MIT Information Quality programs. He is also a professor at MIT Sloan School of Management.

Unlocking the value of data – Allison O’Hair

MIT Sloan Lecturer Allison O'Hair

MIT Sloan Lecturer Allison O’Hair

Compared to five years ago, the amount of data we now generate is huge. Some companies collect that data, but more often than not they don’t do anything with it. Business analytics is an important tool to help organizations harness the power of that data. By unlocking its value, you can do things like improve profits, predict consumer behavior, better understand markets, and make more informed decisions. Most importantly, it can give you a competitive edge.

For those of us in the field of operations research, data analytics is a huge and exciting area. It’s a critical tool for businesses moving forward. As a result, we’re offering MIT Sloan’s popular Analytics Edge course on the MITx online, interactive learning platform this spring. We want to share the cutting-edge knowledge generated at MIT on this important topic with people around the world. Read More »

Save Time on Search Engines: New Algorithm “Grows Lists”–Cynthia Rudin

MIT Sloan Asst. Prof. Cynthia Rudin

Have you ever tried to create a list of all upcoming events in your local area? If you live near Boston, it would be a useful list considering how bad traffic can be when there is a public event like a street festival or fundraising walk.

The problem is that although such events are planned well in advance, there is no online central list of events in Boston. Rather, there are many different sources of event listings, each of which is incomplete, such as Boston.com, Eventbrite and Yelp. Read More »

Cynthia Rudin: Using Data to Predict Your Future Health

MIT Sloan Asst. Prof. Cynthia Rudin

From Huffington Post

Have you ever gone on a trip and unexpectedly found yourself in need of medical care? What if your condition could have been predicted? Better yet, what if you already had the medicine needed to treat that condition in your luggage?

The Hierarchical Association Rule Model (HARM), which I co-developed with Tyler McCormick of the University of Washington and David Madigan of Columbia University, can help patients be better prepared by warning them (and their doctors) about the conditions they may likely experience next. The predictive modeling tool checks data about an individual patient against other patients in the database with similar situations to help determine future conditions. It also alerts patients about any higher risks they may have for certain types of conditions.

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