Impact of body mass index on an initial minimally invasive aortic valve program.

Background: In obese patients, minimally invasive aortic valve replacement (MIS-AVR) presents challenges, and the risk of patient-prosthesis mismatch (PPM) is elevated. This retrospective single-center study evaluates the impact of body mass index (BMI) on the outcome of an initial MIS-AVR program.

Material And Methods: 307 patients underwent MIS-AVR between 01/2013-12/2015, the initial phase of our MIS-AVR program.

Machine Learning Based Classification of Depression Using Motor Activity Data and Autoregressive Model.

Machine learning based disease classification have already achieved amazing results in medicine: for example, models can find a tumor in computer tomography images at least as accurately as experts in the field. Since the development and widespread use of actigraphy watches, activity data has been used as a basis for diagnosing various diseases such as depression or Alzheimer's disease. In this study, we use a dataset with activity measurements of mentally ill and healthy people, calculate various features and achieve a classification accuracy of over 78%.