Dartmouth-Hitchcock granted $1.5M to build AI tech for cancer care

Saeed Hassanpour, PhD, a computer scientist at Lebanon, N.H.-based Dartmouth-Hitchcock Norris Cotton Cancer Center, will use a $1.5 million grant to develop machine learning approaches that use data from medical records to predict lung cancer patients' responses to targeted therapies.

Dr. Hassanpour's team will build and validate information-extraction and machine learning methods that use EHR text information to detect statistically significant connections between medical records, genetic mutations and targeted therapy responses.

The four-year, $1.5 million grant, awarded by the National Cancer Institute, will allow the research team to assess relationships between clinical and pathologic findings, patient genetic profiles and drug resistance. By combining this data, the researchers hope to create improved and personalized treatment strategies for non-small cell lung cancer patients.

"We expect our machine learning methods to identify NSCLC patients with clinically-actionable mutations based on tumor pathology reports and EMR data, and to provide an accurate, fast and inexpensive pre-selection method that can be utilized before performing time-intensive and expensive DNA sequencing to find the same mutations," said Dr. Hassanpour, according to a news release.

More articles on artificial intelligence:
Novant Health implements tech to speed stroke diagnosis
DOD developing algorithm to detect, reduce spread of disease
Houston Methodist deploys AI platform to streamline patient-provider interactions

© Copyright ASC COMMUNICATIONS 2020. Interested in LINKING to or REPRINTING this content? View our policies by clicking here.


Featured Content

Featured Webinars

Featured Whitepapers