Results 141 to 150 of about 52,931 (300)

CYGENT: A cybersecurity conversational agent with log summarization powered by GPT-3 [PDF]

In response to the escalating cyber-attacks in the modern IT and IoT landscape, we developed CYGENT, a conversational agent framework powered by GPT-3.5 turbo model, designed to aid system administrators in ensuring optimal performance and uninterrupted ...
Balasubramanian, Prasasthy, Kostakos, Panos, Seby, Justin   +2 more
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

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

Evaluating The Use of Artificial Intelligence for Issuing Fatwas in Islamic Inheritance Cases: A Juristic Study with A Comparison To Gpt-3.5 [PDF]

: The objective of this research is to explore the potential of Artificial Intelligence, specifically GPT-3, in the process of issuing fatwas within the context of Islamic inheritance law.
Abdulrahman, Manswab Mahsen, Walusimbi, Abdul Hafiz Musa   +1 more
core   +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

Assessing the Accuracy and Reliability of Large Language Models in Psychiatry Using Standardized Multiple-Choice Questions: Cross-Sectional Study

Journal of Medical Internet Research
BackgroundLarge language models (LLMs), such as OpenAI’s GPT-3.5, GPT-4, and GPT-4o, have garnered early and significant enthusiasm for their potential applications within mental health, ranging from documentation support to chat ...
Kaitlin Hanss, Karthik V Sarma, Anne L Glowinski, Andrew Krystal, Ramotse Saunders, Andrew Halls, Sasha Gorrell, Erin Reilly   +7 more
doaj   +1 more source

Question Answering over Linked Data with GPT-3

, 2023
This paper explores GPT-3 for answering natural language questions over Linked Data. Different engines of the model and different approaches are adopted for answering questions in the QALD-9 dataset, namely: zero and few-shot SPARQL generation, as well as fine-tuning in the training portion of the dataset. Answers retrieved by the generated queries and
Faria, Bruno, Perdigão, Dylan, Gonçalo Oliveira, Hugo   +2 more
openaire   +3 more sources

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Performance of large language model in cross-specialty medical scenarios

Journal of Translational Medicine
Background Large language models (LLMs) demonstrate transformative potential in healthcare, yet their diagnostic and therapeutic accuracy across medical specialties remains inadequately characterized.
Zhen Cui, Wuzheng Liu, Xuan Tian, Conglei You, Xiangyu Meng, Huijuan Zhang, Kangzi Gong, Xu Wang, Jun Wu   +8 more
doaj   +1 more source