AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease
Chengsheng Mao(Northwestern University), Yuan Luo(China Railway Group (China)), Robert Vassar(Northwestern University), Borna Bonakdarpour(Northwestern University), Jie Xu(University Town of Shenzhen), Jyotishman Pathak(Mayo Clinic), Luke V. Rasmussen(Northwestern University), Prakash Adekkanattu(Cornell University), Guoqian Jiang(Mayo Clinic), Yikuan Li(Northwestern University), Fei Wang(Sichuan University), Jennifer A. Pacheco(University of Arizona)
Cited by 3
Related Papers
β-Secretase Cleavage of Alzheimer's Amyloid Precursor Protein by the Transmembrane Aspartic Protease BACE
|Science|1999|3.8k
Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data
|Nature Biotechnology|2013|1.1k
Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers
|npj Digital Medicine|2023|651
Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network
|Journal of the American Medical Informatics Association|2013|437