How analytics and machine learning can aid organ transplant decisions – Dimitris Bertsimas and Nikolaos Trichakis

MIT Sloan Prof. Dimitris Bertsimas

MIT Sloan Asst. Prof. Nikolaos (Nikos) Trichakis

From Health Data Management

Imagine this scenario: A patient named John has waited 5.5 years for a much-needed kidney transplant. One day, he learns that a deceased donor kidney is available and that he is the 153rd patient to whom this kidney was offered.

Clearly, this is not a “high-quality” organ if it was declined by 152 patients or the clinicians treating them. But because John has been waiting a long time for a new kidney, should he accept or decline the kidney? And can analytics and machine learning help make that decision easier?

Currently, that decision is usually made by John’s doctor based on a variety of factors, such as John’s current overall health status on dialysis and a gut instinct about whether (and when) John will get a better offer for a healthier kidney.

If John is young and relatively healthy, the risk of prematurely accepting a lower-quality kidney is future organ failure and more surgeries. If John’s health status is critical and he rejects the kidney, he could be underestimating how long it will take until a higher-quality organ is available. The decision could be a matter of life or death.

John’s dilemma isn’t unique in the world of kidney transplantation, where current demand outpaces supply. Since 2002, the number of candidates on the waiting list has nearly doubled, from slightly more than 50,000 to more than 96,000 in 2013. During the same time, live donation rates have decreased. Complicating this problem of supply and demand is an unacceptably high deceased donor organ discard rate, as much as 50 percent in some instances.

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Is this the new class every student should take? – Dimitris Bertsimas

MIT Sloan Prof. Dimitris Bertsimas

From eSchool News

With the high-school graduation season over, it’s time for grads and parents alike to celebrate and relax a bit – and maybe enjoy a long summer before recently minted graduates start college or a new job.

But here is something to contemplate (hopefully not too strenuously) over the coming summer weeks and months: What is the next learning step in the graduate’s preparation for a future career?

Whether a recent graduate plans to study 18th Century English literature in college or jump right into the workforce in any number of jobs, I have a one-word suggestion for them: Data.

Specifically, start learning about the analysis of data.

As seemingly odd as that might sound – perhaps even odder than the elder gentleman who recommends “plastics” to the young Dustin Hoffman character in the classic movie “The Graduate” – the simple fact is that our lives and careers, moving forward, will be increasingly influenced and determined by data analytics in just about every field, from what consumer products we buy to the type of medical treatments our doctors prescribe.

The data analytics era is already here. We see it every time we surf the web and those same pesky advertisements keep following us around, from site to site, no matter how much we try to lose them. Those ads are the result of data-analytic computations by Google and others designed to specifically figure out, mathematically, our consumer interests based on past purchases and web browsing histories.

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Contemplating a career in data science/business analytics? – Dimitris Bertsimas

MIT Sloan Prof. Dimitris Bertsimas

MIT Sloan Prof. Dimitris Bertsimas

From Accepted

Since we recorded this interview, the Wall Street Journal published a short article discussing the strong demand for tech skills around the world. Apparently the area with the greatest gap between supply and demand is Big data/analytics, where 39% of IT leaders feel there is a shortage of people skilled in this area, the highest of any tech field in the survey.

The shortage makes this podcast interview particularly timely because you’ll hear from Dr. Dimitris Bertsimas, Co-Director of MIT Sloan’s Master in Business Analytics, and we discuss this brand new program in depth.

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