Results 151 to 160 of about 1,722,927 (292)

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

Hermeneutical Outlines in and of Dante’s Legal Theory [PDF]

Based upon the concept of Law qualified in Monarchia, II.50, Dante was not only a general philosopher (a lover of knowledge) as well as a political disputant in his times, but also his primary contribution (not always obvious) in legal speculation could ...
Francesco, Cavinato
core  

Rising Pancreatic Cancer Incidence in Young Japanese Women and Increasing Distal Pancreatectomy in Older Adults: A Nationwide Claims‐Based Analysis From 2016 to 2023

Annals of Gastroenterological Surgery, EarlyView.
This nationwide claims‐based study analyzed recent trends in pancreatic cancer incidence (2016–2021) and surgery (2016–2023) in Japan. The study revealed a rising incidence of pancreatic cancer, notably among young women, and an increasing use of distal pancreatectomy among older adults.
Masamitsu Kido, Ryo Morimura, Yusuke Yamamoto, Tomohiro Arita, Shingo Nakashima, Katsutoshi Shoda, Taisuke Imamura, Hidemasa Kubo, Kengo Yoshii, Iichiroh Onishi, Atsushi Shiozaki   +10 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Synthetic Electrocardiogram Spectrogram Generation Using Generative Adversarial Network‐Based Models: A Comparative Study

Advanced Intelligent Systems, EarlyView.
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova, Norelli Schettini, Winston Percybrooks, Begoña García‐Zapirain   +3 more
wiley   +1 more source

Predicting Materials Thermodynamics Enabled by Large Language Model‐Driven Dataset Building and Machine Learning

Advanced Intelligent Systems, EarlyView.
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu, Haydn Anderson, Noah I. Waxman, Vsevolod Kovalev, Byron Fisher, Elizabeth Li, Xiaofeng Guo   +6 more
wiley   +1 more source

SciLitMiner: An Intelligent System for Scientific Literature Mining and Knowledge Discovery

Advanced Intelligent Systems, EarlyView.
SciLitMiner is an intelligent system that federately ingests scientific literature, filters it using advanced information retrieval methods, and applies retrieval‐augmented generation tailored to scientific domains. Demonstrated on creep deformation in γ‐TiAl alloys, SciLitMiner provides a controlled workflow for systematic knowledge discovery and ...
Vipul Gupta, Jonathan David Heaton Paul, Ingo Schmitt, Florian Pyczak   +3 more
wiley   +1 more source

Delivering a family‐based child mental health promotion program among two resettled refugee communities during the COVID‐19 pandemic: Lessons learned in a hybrid type II implementation‐effectiveness randomized controlled trial

American Journal of Community Psychology, EarlyView.
Abstract Background Resettled refugee families face elevated mental health risks, compounded by structural and cultural barriers. The Family Strengthening Intervention for Resettlement (FSIR), co‐developed with resettled refugee communities, aims to improve family functioning and child mental health.
Euijin Jung, Candace Black, Matias Placencio‐Castro, Lila Chamlagai, Rilwan Osman, Morgan Hoffman, William Beardslee, Theresa S. Betancourt   +7 more
wiley   +1 more source

Participation for mental health service development in China: Conditions, challenges, facilitators, and outcomes

American Journal of Community Psychology, EarlyView.
Abstract This study analyzes a participatory project to develop peer support services for people with serious mental illnesses (SMIs) in China. Drawing on interviews with psychiatrists, social workers, service users, and a family caregiver, it examines the conditions, challenges, facilitators, and outcomes of participation in a paternalistic context ...
Zhiying Ma, Yu Fan, Xiyuan Chen, Lindsay Sheehan, Sang Qin, Aoxuan Cao, Liang Zhou   +6 more
wiley   +1 more source