Cynthia Rudin is an Associate Professor of statistics at MIT associated with the Computer Science and Artificial Intelligence Laboratory and the Sloan School of Management. She also directs the Prediction Analysis Lab.
Rudin’s interests are in machine learning, data mining, applied statistics, and knowledge discovery (Big Data). Her application areas are in energy grid reliability, healthcare, and computational criminology. Previously, Rudin was an associate research scientist at the Center for Computational Learning Systems at Columbia University, and prior to that, an NSF postdoctoral research fellow at NYU.
Her team has developed big data analytics tool which gives patient level prediction of the possible recovery after surgery (predicting the number of days in which patient can recover, predicting the recovery path etc.). This is amazing stepping stone in progress of individualized medicine or personalized medicine. Cynthia Rudin and her big data team have used the big data analytics model on random sample of the patients who have undergone a prostatectomy to predict the recovery and possible effect on sexual function of patients after the surgery.
Here is her interview regarding this research –
Similar studies have been done in the past. Here are some examples –
Predicting Benefit From Revascularization in Patients With Ischemic Heart Failure – http://circ.ahajournals.org/content/123/4/444.full
FACTORS PREDICTING RECOVERY OF ERECTIONS AFTER RADICAL PROSTATECTOMY – http://www.sciencedirect.com/science/article/pii/S0022534705669212
- Quantifying and predicting recovery after heart surgery – http://journals.lww.com/psychosomaticmedicine/Abstract/1994/05000/Quantifying_and_predicting_recovery_after_heart.5.aspx
Prediction of Improvement of Regional Left Ventricular Function After Surgical Revascularization – http://circ.ahajournals.org/content/91/11/2748.short
- A Model for Early Prediction of Facial Nerve Recovery After Vestibular Schwannoma Surgery – http://journals.lww.com/otology-neurotology/Abstract/2011/07000/A_Model_for_Early_Prediction_of_Facial_Nerve.19.aspx
Comparison of Myocardial Contrast Echocardiography and Low-Dose Dobutamine Stress Echocardiography in Predicting Recovery of Left Ventricular Function After Coronary Revascularization in Chronic Ischemic Heart Disease – http://circ.ahajournals.org/content/92/10/2863.short
But, this is first research which is unique attempt at individualized medicine leveraging big data analytics.