Results 201 to 210 of about 81,815 (304)

Inferring rheumatoid arthritis disease activity status from the electronic health records across health systems

Arthritis &Rheumatology, Accepted Article.
Objective Disease activity plays a central role in rheumatoid arthritis (RA) clinical studies. The inconsistent availability of data on disease activity in real‐world electronic health records (EHR) data has limited the ability to generate real‐world evidence (RWE). This study aimed to develop and validate scalable machine learning (ML) models to infer
David Cheng, Xuan Wang, Gregory C. McDermott, Jennifer S. Hanberg, Zoe Love, Katherine Zhong, Mary Jeffway, Jue Hou, Vidul Panickan, Rahul Sangar, Ying Qi, Connor Melley, Lauren Costa, Dakota Feil, Rachael Matty, Dana Weisenfeld, Abisayo Animashaun, Aimee Schreiner, Sara Morini, Lauren Rusnak, Andrew Cagan, Misti Paudel, J. Michael Gaziano, Brian Sauer, Michael Weinblatt, Joshua Baker, Bryant England, Yuk‐Lam Ho, Kelly Cho, Paul Monach, Grant W. Cannon, Nancy Shadick, Ted R. Mikuls, Tianxi Cai, Katherine P. Liao   +34 more
wiley   +1 more source

When Large Language Models (LLMs) walk into a Bachelor's in optometry examination: Comparing the performances of LLMs and bachelor of optometry students. [PDF]

Indian J Ophthalmol
Arora A, Parmar UPS, Anjali, Mathur P, Kishore K, Singh U, Pandav SS, Gupta V.   +7 more
europepmc   +1 more source

ChatGPT for complex text evaluation tasks

Journal of the Association for Information Science and Technology, Volume 76, Issue 4, Page 645-648, April 2025.
Abstract ChatGPT and other large language models (LLMs) have been successful at natural and computer language processing tasks with varying degrees of complexity. This brief communication summarizes the lessons learned from a series of investigations into its use for the complex text analysis task of research quality evaluation.
Mike Thelwall
wiley   +1 more source

ClinicRealm: Re-evaluating large language models with conventional machine learning for non-generative clinical prediction tasks. [PDF]

NPJ Digit Med
Zhu Y, Gao J, Wang Z, Liao W, Zheng X, Liang L, Bernabeu MO, Wang Y, Yu L, Pan C, Harrison EM, Ma L.   +11 more
europepmc   +1 more source

Annotating aspects in text and image: A new task and dataset for multimodal aspect‐based sentiment analysis

Journal of the Association for Information Science and Technology, EarlyView.
Abstract Aspect‐Based Sentiment Analysis (ABSA) has evolved from textual analysis to a multimodal paradigm, integrating visual information to capture nuanced sentiments. Despite advancements, existing Multimodal ABSA (MABSA) research remains limited in granularity, which focuses on either coarse‐level categories or named entities, neglecting fine ...
Li Yang, Jia Yang, Jin‐Cheon Na, Jianfei Yu   +3 more
wiley   +1 more source

Small LLMs can be good coldstart recommenders. [PDF]

Front Artif Intell
Noel J, Monterola C, Tan DS.
europepmc   +1 more source

Context‐centric proactive information delivery for Knowledge Work support: Opportunities, challenges, and directions. An Annual Review of Information Science and Technology (ARIST)

Journal of the Association for Information Science and Technology, EarlyView.
Abstract Context‐centric proactive information delivery (PID) is a relatively underexplored domain within recommender systems (RS) aimed at enhancing Knowledge Workers' productivity by proactively providing relevant information during digital tasks.
Mahta Bakhshizadeh, Christian Jilek, Markus Schröder, Heiko Maus, Andreas Dengel   +4 more
wiley   +1 more source

Accelerating real-world data collection using large language models in rare neoplasms: a bone sarcoma example. [PDF]

ESMO Real World Data Digit Oncol
Teterycz P, Rynkun S, Szostakowski B, Wągrodzki M, Rutkowski P, Rosińska M.   +5 more
europepmc   +1 more source

A dancing bear, a colleague, or a sharpened toolbox? The cautious adoption of generative artificial intelligence technologies in digital humanities research

Journal of the Association for Information Science and Technology, EarlyView.
Abstract The emergence of generative artificial intelligence (GenAI) is reshaping the research landscape and carries significant implications for Digital Humanities (DH), a field long intertwined with computational methods and technologies. This study examines how DH scholars are adopting and critically evaluating GenAI in their research. Drawing on an
Rongqian Ma, Meredith Dedema, Andrew Cox
wiley   +1 more source

Large language models for primary care ophthalmic education: a systematic review. [PDF]

Front Med (Lausanne)
Li S, Wang X, Chen Y, Tian M, Lin P, Lai M, Jiang L.   +6 more
europepmc   +1 more source