Speaker Profile

Founder and CEO, Humanitics

Hiren Shah has more than 20 years in the field of Information Technology and was one of the early starters in 1996 during the dot com era. He possesses vast knowledge and experience as a Data Scientist with Hitachi Data Systems, where he was frequently dealing with processing of Petabytes of Data mining and exploration of sensitive information within defined processing times. He founded Humanitics, a Visual Data Analytics company for enabling A.I based algorithms to assist providers in preclinical decisions within EHR/EMR Workflows. He along with his team has developed an API which can be easily plugged into exsisting EHR/EMR systems. The web based application maps various tests, genes and drugs with selected disease with a pathfinding algorithm and exploratory analysis with a visual approach which removes the complexity of reading and understanding huge textual information by the providers before arriving at a clinical decision for a patient.

AI & Data Science Showcase:

An A.I Driven Visual Analytics pre Clinical Decision support tool which uses complex pathfinding methods to visualize disease, genes, drug targets, Lab tests for exsistings EHR/EMR.

Precision Healthcare through Visual Analytics
Humanitics has developed pathfinding algorithms to identify disease patterns and assists providers through clinical decision support system an indepth understanding of Disease, Gene, Drug Targets and Path Lab information. Finding the right drug, gene and test has always been a challenge to the Providers which gets addressed by enabling EHRs and EMRs to integrate and connect Providers and Patients to various stakeholders in the Healthcare Ecosystem.

 Session Abstract – PMWC 2020 Silicon Valley

The PMWC 2020 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.