Results 181 to 190 of about 63,129 (302)

Potential for use of Al/machine learning for pharmacovigilance: Is there a role for regulators?

British Journal of Clinical Pharmacology, EarlyView.
Christina Gao, Ashley M. Hopkins, Andrew Rowland, Stephen Bacchi   +3 more
wiley   +1 more source

AI Hallucinations in Tourism: How Errors Impact Consumer Trust and Recommendation Acceptance

Journal of Consumer Behaviour, EarlyView.
ABSTRACT Generative artificial intelligence (GenAI) is quickly transforming travel planning; however, its outputs can include hallucinations, which are plausible yet false statements that can undermine user judgement. Eliminating hallucinations in GenAI technology is currently impossible.
Francisco Rejón‐Guardia, Sebastian Molinillo, Rafael Anaya‐Sánchez   +2 more
wiley   +1 more source

Innovation and application of Large Language Models (LLMs) in dentistry - a scoping review. [PDF]

BDJ Open
Umer F, Batool I, Naved N.
europepmc   +1 more source

GP or ChatGPT? Ability of large language models (LLMs) to support general practitioners when prescribing antibiotics. [PDF]

J Antimicrob Chemother
Ngoc Nguyen O, Amin D, Bennett J, Hetlevik Ø, Malik S, Tout A, Vornhagen H, Vellinga A.   +7 more
europepmc   +1 more source

Improving Genotype Imputation in High‐Dimensional Pharmacogenomics Using Multiple Imputation: Evaluation with Machine Learning Approaches

Clinical Pharmacology &Therapeutics, EarlyView.
Multiple imputation is well‐established for handling missing data, yet its use in high‐dimensional genetic datasets remains limited. Using pharmacokinetic tuberculosis simulations and SNP data (1000 Genomes Project), we compared machine learning (ML) and traditional approaches (e.g., mean imputation and complete‐case analysis) for imputation and ...
Innocent G. Asiimwe, Tao You, Daniel F. Carr, Munir Pirmohamed, Geraint Davies, Andrea L. Jorgensen, on behalf of the UNITE4TB Consortium   +6 more
wiley   +1 more source

Enhancing stock timing predictions based on multimodal architecture: Leveraging large language models (LLMs) for text quality improvement. [PDF]

PLoS One
Chen M, Tang Y, Qi Q, Dai H, Lin Y, Ling C, Li T.   +6 more
europepmc   +1 more source

What Can K–12 Education Teach College Professors?

The Bulletin of the Ecological Society of America, EarlyView.
Michael P. Marchetti
wiley   +1 more source

Engineered Metal–Organic Frameworks‐Based Materials for Environmental Detection

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Engineered metal–organic frameworks (MOFs) regulated by various material modification strategies are discussed for environmental contaminant detection under different sensing mechanisms, providing future improvements of MOFs in environmental detection. Sensitive and selective detection of contaminants is crucial for environmental protection.
Pan Gao, Song Wang, Yuechao Yao, Yibo Dou   +3 more
wiley   +1 more source

Augmenting research consent: should large language models (LLMs) be used for informed consent to clinical research? [PDF]

Res Ethics
Allen JW, Schaefer O, Mann SP, Earp BD, Wilkinson D.   +4 more
europepmc   +1 more source

A call for ethical, equitable, and effective artificial intelligence to improve care for all people with epilepsy: A roadmap. A report by the ILAE Global Advocacy Council and Big Data Commission

Epilepsia, EarlyView.
Abstract The artificial intelligence (AI) revolution is upon us. It will inevitably form a central component of epilepsy workflows and patient advocacy. Therefore, it behooves us as health care providers to ride the crest of this wave and guide its direction for the benefit of all people with epilepsy.
Colin B. Josephson, Sandor Beniczky, Spiros Denaxas, Akio Ikeda, Lara Jehi, Angelina Kakooza Mwesige, Nathalie Jette, Gabriel Davis Jones, Philippe Ryvlin, Arjune Sen, Chahnez Charfi Triki, Gabriella Waters, Alla Guekht, J. Helen Cross   +13 more
wiley   +1 more source