Mohammed is a researcher, computer scientist, programmer and data scientist who earned his PhD in computer science in 2014 from the University of Missouri. He joined Georgia Tech Computational Science and Enginerring school and Emory University as Postdoctoral Fellow to work on predictive modeling in healthcare. His research included predictive modeling, relational cluster analysis, health and nursing informatics. Currently, he is an Applied Scientist at Amazon working on Comprehend Medical, a natural language processing (NLP) service that leverages state-of-the-art machine learning techniques for extracting relationships and entities including medical conditions, medications, treatment, test and procedures.
PhD in Computer Science, 2014
University of Missouri
BS in Computer Science, 2005
University of Missouri
Comprehend Medical is a natural language processing (NLP) service that leverages state-of-the-art machine learning techniques for extracting relationships and entities including medical conditions, medications, treatment, test and procedures.
We implemented a cloud-based predictive modeling system via a hybrid setup combining a secure private server with the Amazon Web Services (AWS) Elastic MapReduce platform. EHR data is preprocessed on a private server and the resulting event sequences are hosted on AWS
Grouping patients can play an important role in designing clinical trials or improving care delivery. In this paper, we present a method for stratifying patients based on their ADL scores.
Advanced Development of an Open-source Platform for Web- based Integrative Digital Image Analysis in Cancer
he aim is to build a reliable prediction model for predicting the optimal treatment of an epilepsy patient.
This research identifies specific care coordination activities used by Aging In Place (AIP) nurse care coordinators and home healthcare nurses when coordinating care for older community dwelling adults and suggests a method to quantify care coordination.
Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard.
I served as an instructor and teaching assistant for the following courses at Georgia Tech:
I served as an instructor and teaching assistant for the following courses at the University of Missouri: