KidneyAI: Point-of-care software application for assessment of renal diseases

Spring 2018 RESEARCH INCUBATION AWARDEE

PI: Vijaya Kolachalama, Assistant Professor, Computational Biomedicine, MED

Co-PI(s): Vipul Chitalia, Assistant Professor, Medicine, MED;  Joel Henderson, Associate Professor & Pathology & Laboratory Medicine, School of Medicine

The challenge

The renal disease requires timely diagnosis and design monitoring schedules to eliminate possibilities of fatalities among the patient. Renal disease is a complicated ailment that complicates the normal body functioning making the patient susceptible to diabetes, hypertension, and kidney failure. Point-of-care software, therefore, examines the risk factors and early diagnosis, which is significant for the patient’s quality of life. Consequently, monitoring is done by the software, which may register a reduction in dialysis and transplant.

Solution

Physicians disseminate information after careful examinations and consultation with patients through the software. As such, monitoring of the renal disease is structured, taking into consideration the risk factors likely to emerge. Therefore information concerning medication and test results are shared.

The Process

Modules for albuminuria and protein verification must be set. This is done to obtain results that will classify renal diseases. After that classification will help determine the risk factors, and finally, an in-depth analysis will be done to come up with relevant treatment procedures for the renal condition.