Intelligent Healthcare Management

Healthcare management through the use of computing is a considerable novelty in the medical field. Designing and implementing intelligent solutions in an efficient manner to realize optimal healthcare is a significant concern.

At present the center is involved in designing optimal machine learning (ML) solutions for the prediction of acute lymphoblastic leukemia (ALL) in children. The work has resulted in a publication in a renowned journal founded by Johns Hopkins Medical Center in the U.S.

The center has also been working towards an Internet of Bio-Nano Things (IoBNT) based disease monitoring and drug release system. Further details on this are available in the related publication.

Android cardiac monitoring application was previously designed employing mobile cyber physical system principles for cardiac monitoring, helping patients and physicians alike. The system automates planning of regular check-ups for cardiac patients by taking readings of blood pressure, heart rate and oxygen level and keeps the physicians updated about the current heart health status of the respective patient. The designed mobile cyber physical system for cardiac monitoring is an Android based application that helps patients to check their health status on regular basis. Photo plethysmography (PPG), is used to identify blood flow variability from built-in phone camera and flashlight. The deployed system uses machine learning algorithms to validate cardiac information (including blood pressure, heart rate and blood oxygen level stored in patient records) based on prior case history. In case of anomalies, the application automatically notifies the physician as well as indicate any anticipated anomalies in near future.