Results 171 to 180 of about 239,466 (252)

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

Measuring the Burden of Choice: Development and Validation of a Choice Overload Scale

Journal of Consumer Behaviour, EarlyView.
ABSTRACT Excessive choice imposes substantial cognitive demands on consumers, impair decision‐making, and generate negative consumer responses—a phenomenon widely known as the choice overload effect. Despite its conceptual prominence in consumer research and its enduring relevance in today's consumer markets, existing approaches to measuring choice ...
Jennifer Musial
wiley   +1 more source

Assessment of Large Language Models (LLMs) in decision-making support for gynecologic oncology. [PDF]

Comput Struct Biotechnol J
Gumilar KE, Indraprasta BR, Faridzi AS, Wibowo BM, Herlambang A, Rahestyningtyas E, Irawan B, Tambunan Z, Bustomi AF, Brahmantara BN, Yu ZY, Hsu YC, Pramuditya H, Putra VGE, Nugroho H, Mulawardhana P, Tjokroprawiro BA, Hedianto T, Ibrahim IH, Huang J, Li D, Lu CH, Yang JY, Liao LN, Tan M.   +24 more
europepmc   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

Carbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao, Fei Wang, Qixuan Cai, Aike Xi, Kangkang Wang, Khaixien Leu, Rufan Zhang   +6 more
wiley   +1 more source

Porous Carbon Materials for Carbon Dioxide Capture

Carbon Energy, EarlyView.
This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu, Chuhan Fu, Tao Qi, Hui Zhou, Guangping Hao, Yalou Guo, Guoping Hu   +6 more
wiley   +1 more source

The role of artificial intelligence in medical education: an evaluation of Large Language Models (LLMs) on the Turkish Medical Specialty Training Entrance Exam. [PDF]

BMC Med Educ
Koçak M, Oğuz AK, Akçalı Z.
europepmc   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

A Comprehensive Analysis of a Social Intelligence Dataset and Response Tendencies Between Large Language Models (LLMs) and Humans. [PDF]

Sensors (Basel)
Mori E, Qiu Y, Kataoka H, Aoki Y.
europepmc   +1 more source

Chemie.KI – Automatisierte Aufgabenbewertung durch trainierte KI‐Modelle

CHEMKON, EarlyView.
In Schule und Hochschule bearbeiten Lernende in der Regel mehr Aufgaben, als Lehrende korrigieren können. Wo der Mensch an seine Grenzen kommt, kann Künstliche Intelligenz (KI) ansetzen und bei Routineaufgaben unterstützen oder sie auch ganz übernehmen.
Timm Wilke
wiley   +1 more source

AI‐Enabled Precision Dosing in Pediatrics: Enhancing Model‐Informed Decision Making

Clinical Pharmacology &Therapeutics, EarlyView.
Ensuring safe and effective pharmacotherapy for children remains a central challenge in clinical pharmacology, yet rapid advances in AI have not translated into clinical practice. This Perspective highlights how AI‐enabled approaches can enhance model‐informed decision making for precision dosing.
Kei Irie, Tomoyuki Mizuno
wiley   +1 more source