Researchers from MIT and the Massachusetts General Hospital are looking to create a new system that stores video files from Laparoscopy surgery in a more efficient way. Their new system would be able to recognize different parts of the surgery like tissue removal, stapling, biopsy, etc. and store the data accordingly. The system can also be trained to predict which medical instrument is needed next and alert the surgeon if there are any issues arising. However, the system must try to approximate the data that is left out when the frames of the video are slightly altered. However, with the machine learning these new things, it can create a very efficient way of surgery.

This article follows a group of mathematicians from the University of Twente teamed with researchers from University Medical Center Utrecht that set out to help neuroscience by simulating the brain to determine which parts of the brain need to be removed that cause people to suffer from epilepsy. The study takes place in the Netherlands where out of the 100000 people who suffer from epilepsy only 2/3rds of the people respond to the medicinal treatment and the other 1/3rd require parts of their brain to be removed. The difficulty with this procedure is that it is not always clear which specific part of the brain needs to be removed. The mathematicians and researchers have found using computer simulation that the “abnormal” parts of the brain are not always the parts that need to be removed. The computer program allows the researcher to experiment as much as they would like and in the real world they only have one chance.