Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My Custom Filters

Publication date

Text availability

Article attribute

Article type

Additional filters

Article Language

Species

Sex

Age

Other

Search Results

27 results

Filters applied: . Clear all
Results are displayed in a computed author sort order. The Publication Date timeline is not available.
Page 1
Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort.
Westwood S, Baird AL, Anand SN, Nevado-Holgado AJ, Kormilitzin A, Shi L, Hye A, Ashton NJ, Morgan AR, Bos I, Vos SJB, Baker S, Buckley NJ, Ten Kate M, Scheltens P, Teunissen CE, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lléo A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Legido-Quigley C, Bertram L, Barkhof F, Zetterberg H, Morgan BP, Streffer J, Visser PJ, Lovestone S. Westwood S, et al. Among authors: kormilitzin a. J Alzheimers Dis. 2020;74(1):213-225. doi: 10.3233/JAD-190434. J Alzheimers Dis. 2020. PMID: 31985466 Free PMC article.
Med7: A transferable clinical natural language processing model for electronic health records.
Kormilitzin A, Vaci N, Liu Q, Nevado-Holgado A. Kormilitzin A, et al. Artif Intell Med. 2021 Aug;118:102086. doi: 10.1016/j.artmed.2021.102086. Epub 2021 May 18. Artif Intell Med. 2021. PMID: 34412834
A direct application of the trained NER model to CRIS data resulted in reduced performance of F1 = 0.762, however after fine-tuning on a small sample from CRIS, the model achieved a reasonable performance of F1 = 0.944. ...The resulting model and the pre-trai
A direct application of the trained NER model to CRIS data resulted in reduced performance of F1 = 0.762, however after fine-tuning o
27 results