Early Screening for Autism with Data Science Can Change Lives

Abstract: Early screening for cognitive health development disorders among children is a novel and challenging application domain to predictive modeling techniques.

We present the challenges, solutions, insights, and results of our user-facing solution that screens for autism by combining multiple predictors based on multiple media inputs, while allowing for inconclusive determination on hard-to-screen subjects.

Outline:
▪ Using predictive modeling techniques for early screening for cognitive health development disorders among children
▪ The challenges, solutions, insights, and results of our user-facing machine learning solution that screens for autism
▪ How do you combine predictors based on multiple media inputs - including video and datasets - for hard-to-screen subjects

Bio: Halim is a high tech innovator who spearheaded world-class data science projects at game changing techs like eBay and Teradata. Formally educated in Machine Learning, his professional expertise span Information Retrieval, Natural Language Processing, and Big Data. Halim has a proven track record of applying state of the art data science techniques across industry verticals such as eCommerce, web & mobile services, airline, BioPharma, and the medical technology industry. He currently leads the Data Science team at Cognoa, a data driven behavioral healthcare startup in Palo Alto.

Open Data Science Conference