סמינר בניהול טכנולוגיה ומערכות מידע

Ofir Ben-Assuli, Associate Professor in the Faculty of Business Administration at Ono Academic College

09 במרץ 2021, 12:00 
זום 
סמינר בניהול טכנולוגיה ומערכות מידע

“Stratifying Individuals into Non-Alcoholic Fatty Liver Disease Risk Levels using Time Series Machine Learning Models”

Abstract: Non-alcoholic fatty liver disease (NAFLD) affects 25% of the general population worldwide. While most NAFLD patients are asymptomatic, NAFLD may progress to fibrosis and later into cirrhosis, cardiovascular disease and diabetes. We stratified patients' risks for NAFLD and advanced fibrosis from 2007 to 2017 by modeling the fibrosis risk in 5,579 individuals (from a main Israeli hospital). Time-series machine learning models (Hidden Markov Models and Group-Based Trajectory Models) profiled fibrosis risk by modeling patients’ latent medical status (resulted in three groups). Few works on NAFLD fibrosis have monitored individuals after the first visit. Our results, however, show the substantial value in considering all visits and discovering the latent medical state of each individual and its risk level. We show that individuals in the high-risk group had more abnormal lab test values and an increasing prevalence of chronic conditions (e.g. hypertension and diabetes). Classification models with the group information showed that they significantly improved risk fibrosis prediction. These findings suggest that longitudinal risk assessment (optionally accessed via EMR/EHR) enables early identification of specific individual groups exhibiting distinct medical trajectories based on their routine visits. Then, it may be used to make population-specific medical recommendations to avoid the progression of chronic disease and its complications. Incorporating unique machine learning methods into the analytics of IS papers is considered highly advisable and our work underscores the value of such data science components for IS researchers and managers.

 

 

https://us02web.zoom.us/j/85645534841?pwd=cnFNM2dqa0NHT01yM2Nnd3VlWDdRQT09

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