Results 101 to 110 of about 141,350 (263)

Assessing the proficiency of large language models in automatic feedback generation: An evaluation study

Computers and Education: Artificial Intelligence
Assessment feedback is important to student learning. Learning analytics (LA) powered by artificial intelligence exhibits profound potential in helping instructors with the laborious provision of feedback.
Wei Dai, Yi-Shan Tsai, Jionghao Lin, Ahmad Aldino, Hua Jin, Tongguang Li, Dragan Gašević, Guanliang Chen   +7 more
doaj   +1 more source

Is Precision Agriculture Technology Adoption Persistently Overestimated?

Agribusiness, EarlyView.
ABSTRACT Precision agriculture is sometimes assumed to diffuse steadily over time, and industry planning frequently extrapolates early adoption trends forward. This study evaluates the accuracy of such expectations by comparing agricultural input dealers' forecasts of future service offerings with the actual levels of offerings that dealerships ...
Trey Malone, Chad Fiechter, Zanliang Meng, James Lowenberg‐DeBoer, Bruce Erickson, Jay Akridge   +5 more
wiley   +1 more source

An exploratory assessment of GPT-4o and GPT-4 performance on the Japanese National Dental Examination

Saudi Dental Journal
Background and Objectives: Multiple large language models (LLMs) have been released since 2022, including OpenAI’s GPT-3.5 and GPT-4. The latest model, GPT-4o, introduced on May 13, 2024, significantly improves GPT-4.
Masaki Morishita, Hikaru Fukuda, Shino Yamaguchi, Kosuke Muraoka, Taiji Nakamura, Masanari Hayashi, Izumi Yoshioka, Kentaro Ono, Shuji Awano   +8 more
doaj   +1 more source

General Purpose Technologies and their Implications for International Trade [PDF]

General purpose technologies (GPTs) are drastic innovations, such as electrification, the transistor, and the Internet, that are characterized by the pervasiveness in use, innovational complementarities, and technological dynamism.
Petsas, Iordanis
core   +1 more source

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

Annals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo, Masanori Tokunaga, Hiroyuki Yamamoto, Hideki Ueno, Yusuke Kinugasa   +4 more
wiley   +1 more source

Evaluation of reliability, repeatability, and confidence of ChatGPT for screening, monitoring, and treatment of interstitial lung disease in patients with systemic autoimmune rheumatic diseases

Digital Health
Background In recent years, potential applications of ChatGPT in medication-related practices have drawn great attention for its intuitive user interfaces, chatbot, and powerful analytical capabilities.
Minjie Lin, Chuanjun Xu, Xiang Qu, Biyun Xu, Yanghong Wang, Ruyi Zou, Yingwei Zhang   +6 more
doaj   +1 more source

A multiscale Bayesian optimization framework for process and material codesign

AIChE Journal, EarlyView.
Abstract The simultaneous design of processes and enabling materials such as solvents, catalysts, and adsorbents is challenging because molecular‐ and process‐level decisions are strongly interdependent. Sequential approaches often yield suboptimal results since improvements in material properties may not translate into superior process performance. We
Michael Baldea
wiley   +1 more source

Trauma triage performance of large language models on raw Turkish emergency notes: Artificial intelligence versus human expertise

Hong Kong Journal of Emergency Medicine
Objectives Large language models, such as GPT‐4o, have demonstrated potential in clinical decision‐making; however, their reliability in high‐stakes environments, including emergency department triage, remains uncertain.
İbrahim Sarbay, Melike Mercan Başpinar, Keith Grimes, Asım Bedri Erdem, Yunus Emre Gemici, Taha Yilmaz, Alper Görkem Çimen, Fatih Aslan, Mustafa Çalik   +8 more
doaj   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source