Melax Tech, a provider of biomedical natural language processing (NLP) technology, and Brigham and Women’s Hospital, an academic medical center in Boston, has been awarded a two-year $2.5 million grant by the NIH. The project aims to build and validate a clinical decision support system (CDS) for early cognitive decline detection. The study will use advanced deep learning and NLP algorithms to identify patients with cognitive decline signals from electronic health records (EHRs) and improve early diagnosis in primary care settings.
The project will focus on two main objectives:
“This award is a recognition of our clinical NLP technologies. We will develop cutting-edge NLP algorithms to identify at-risk patients and extract cognitive concerns, symptoms, diagnosis, assessments, and social determinants of health (SDoH) factors from clinical notes. We are very excited to work closely with our clinical collaborators on implementing and validating these NLP algorithms,” said Dr. Jingcheng Du, NLP Director at Melax Tech and Principal Investigator on this award.
“Early intervention for Alzheimer’s is crucial with the projected increase in affected Americans and the corresponding cost of care. Our deep learning-based CDS aims to revolutionize primary care diagnosis and management and improve early detection accuracy for better patient outcomes,” says Dr. Frank Manion, VP for Innovations at Melax Tech.
“This study is a critical step in our mission to improve the lives of those affected by Alzheimer’s disease and related dementia,” said lead researcher Dr. Li Zhou of Brigham and Women’s Hospital. “Using deep learning algorithms and electronic health records can revolutionize how we approach early detection and intervention for AD/ADRD.”
This project is supported by the National Institute On Aging of the National Institutes of Health under Award Number R44AG081006. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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