Results 171 to 180 of about 2,800,552 (286)

Low-energy small language models with retrieval-augmented generation can surpass large-model performance in rheumatology. [PDF]

Front Med (Lausanne)
Felde S, Buchkremer R, Chehab G, Thielscher C, Distler JHW, Schneider M, Richter JG.   +6 more
europepmc   +1 more source

Does AI at Work Increase Stress? Text Mining Social Media About Human–AI Team Processes and AI Control

Journal of Organizational Behavior, Volume 47, Issue 8, Page 1423-1437, October 2026.
ABSTRACT With rising use of artificial intelligence (AI) in organizations, alongside increasing mental health issues, we seek to understand how AI use affects human stress. Drawing on the automation–augmentation perspective, we propose that AI control over decision‐making thwarts human autonomy and thus contributes to stress.
Florian Klonek, Sharon Parker
wiley   +1 more source

Patient Cognitive Bias in Large Language Model-Supported Health Consultations: Simulation-Based Comparative Study. [PDF]

J Med Internet Res
Zuo Y, Wan Q, Wang S.
europepmc   +1 more source

Interrogating the Escherichia coli Epitranscriptome Via CRISPR Interference and Nanopore Native RNA Sequencing

MicrobiologyOpen, Volume 15, Issue 5, October 2026.
Epitranscriptomics is understudied in bacteria but has the ability to modulate antimicrobial resistance, virulence and pathogenicity. Pitt et al. implement two cutting‐edge techniques: CRISPR interference and Nanopore direct RNA sequencing along with functional assays to study RNA modifications in Escherichia coli.
Miranda E. Pitt, Jianshu Zhang, An N. T. Nguyen, Michael B. Hall, Leila Jebeli, Leo A. Featherstone, Garry S. A. Myers, Nichollas E. Scott, Lachlan J. M. Coin   +8 more
wiley   +1 more source

The use and methodological reporting of large language models in qualitative research: a scoping review. [PDF]

BMC Med Res Methodol
Kempny C, Frings J, Rust P, Meister S, Fehring L.   +4 more
europepmc   +1 more source

Retrieve-Then-Verify for Evaluating Evidence Support and Hallucination in Large Language Model-Generated Medical Information: Empirical Study. [PDF]

JMIR AI
Liang Z, Sheffield C, Butera G, Antani S.   +3 more
europepmc   +1 more source

Methods for Uncertainty Quantification in Dictionary Matching to Advance Reliability of Quantitative MRI

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1956-1971, October 2026.
ABSTRACT Aims Purpose: Dictionary matching is a standard tool in quantitative MRI (qMRI), but typically lacks uncertainty quantification (UQ). This is critical when advanced reconstructions (e.g., compressed sensing, deep learning) introduce complex‐valued, spatially varying, and temporally correlated noise that violates standard assumptions of ...
Brian Toner, Ute Goerke, Eze Ahanonu, Kevin Johnson, Vibhas Deshpande, Holden H. Wu, Maria I. Altbach, Ali Bilgin   +7 more
wiley   +1 more source

The <i>Arabidopsis</i> FRIENDLY (FMT) protein interacts with NAC and determines where nuclear-encoded mitochondrial proteins are translated. [PDF]

Proc Natl Acad Sci U S A
Montoya-Brach V, Roignant J, Renard G, Chicher J, Duchêne AM.   +4 more
europepmc   +1 more source

Zero‐Shot Self‐Supervised Learning of Single Breath‐Hold Magnetic Resonance Cholangiopancreatography (MRCP) Reconstruction

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1666-1681, October 2026.
ABSTRACT Purpose To investigate the feasibility of zero‐shot self‐supervised learning reconstruction for reducing breath‐hold times in magnetic resonance cholangiopancreatography (MRCP). Methods Breath‐hold MRCP was acquired from 11 healthy volunteers on 3T scanners using an incoherent k‐space sampling pattern, leading to a 14‐s acquisition time and an
Jinho Kim, Marcel Dominik Nickel, Florian Knoll   +2 more
wiley   +1 more source

Measuring and mitigating debugging effectiveness decay in code language models. [PDF]

Sci Rep
Adnan M, Kuhn CCN.
europepmc   +1 more source