Results 161 to 170 of about 2,420,708 (306)
Objective This systematic review aimed to assess the diagnostic accuracy of algorithms used to identify rheumatoid arthritis and juvenile idiopathic arthritis in electronic health records. Methods We searched Medline, Embase, and Cochrane Central Register for Controlled Trials databases and included studies that validated case definitions against a ...
Constanza Saka‐Herrán +10 more
wiley +1 more source
Evidence Against Syntactic Encapsulation in Large Language Models. [PDF]
McGee TA, Zhang Y, Blank IA.
europepmc +1 more source
SEMbeddings: how to evaluate model misfit before data collection using large-language models
Tommaso Feraco, Enrico Toffalini
openalex +2 more sources
Objective We aimed to test the efficacy of personalized treatment of older veterans with chronic low back pain (CLBP) delivered by Aging Back Clinics (ABCs) as compared with usual care (UC). Methods Two hundred ninety‐nine veterans aged 65 to 89 with CLBP from three Veterans Affairs (VA) medical centers underwent baseline testing, randomization to ABC ...
Debra K. Weiner +9 more
wiley +1 more source
Large language models for neurology: a mini review. [PDF]
Wunsch Iii DC, Hier DB.
europepmc +1 more source
Neural Re-Contextualization for Dynamic Semantic Control in Large Language Models [PDF]
Florentine Hawks +3 more
openalex +1 more source
Objective A patient‐centered approach for chronic disease management, including systemic lupus erythematosus (SLE), aligns treatment with patients’ values and preferences, leading to improved outcomes. This paper summarizes how patient experiences, perspectives, and priorities informed the American College of Rheumatology (ACR) 2024 Lupus Nephritis (LN)
Shivani Garg +20 more
wiley +1 more source
Artificial intelligence, large language models, and you
Charles Marquardt, MD
doaj +1 more source
Applications of Large Language Models in Glaucoma: A Scoping Review. [PDF]
Rubegni G +8 more
europepmc +1 more source
Large Causal Models from Large Language Models
We introduce a new paradigm for building large causal models (LCMs) that exploits the enormous potential latent in today's large language models (LLMs). We describe our ongoing experiments with an implemented system called DEMOCRITUS (Decentralized Extraction of Manifold Ontologies of Causal Relations Integrating Topos Universal Slices) aimed at ...
openaire +2 more sources

