Results 121 to 130 of about 48,609 (342)

Psoas Muscle Volume as a Predictor of Postoperative Complications in Patients Undergoing Emergency Surgery for Strangulated Small Bowel Obstruction: A Retrospective Single‐Center Study

Annals of Gastroenterological Surgery, EarlyView.
This retrospective study identified low preoperative psoas muscle volume, measured by computed tomography, as an independent predictor of postoperative complications in patients undergoing emergency surgery for strangulated small bowel obstruction. Low psoas muscle volume, particularly in older adults, was associated with cardiopulmonary and systemic ...
Takuya Shiraishi, Chika Katayama, Yuta Shibasaki, Chika Komine, Takuhisa Okada, Akihiko Sano, Makoto Sakai, Hiroomi Ogawa, Ken Shirabe, Hiroshi Saeki   +9 more
wiley   +1 more source

Extralevator Abdominoperineal Excision Improves Overall Survival Compared to Standard Abdominoperineal Excision: A Systematic Review and Meta‐Analysis

Annals of Gastroenterological Surgery, EarlyView.
This systematic review and meta‐analysis of 38 studies, encompassing over 5000 patients, compared extralevator abdominoperineal excision (ELAPE) with standard abdominoperineal excision (APE) in patients with advanced low rectal cancer. ELAPE was associated with significantly improved overall and disease‐free survival, reduced intraoperative perforation
Sarolta Beáta Kávási, Diana‐Elena Floria, Anett Rancz, Dániel Sándor Veres, Nándor Faluhelyi, Pál Miheller, Péter Hegyi, Szabolcs Ábrahám   +7 more
wiley   +1 more source

Automata, formal languages abstract switching, and computability in a Ph.D. computer science program [PDF]

, 1968
Robert McNaughton
openalex   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +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

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

Automata Theory and Formal Languages

, 2008
In this book we present some basic notions and results on Automata Theory, For- mal Language Theory, Computability Theory, and Parsing Theory. In particular, we consider the class of regular languages which are related to the class of finite automata, and the class of the context-free languages which are related to the class of pushdown automata.
openaire   +3 more sources

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

The Insistence of Blackness and the Persistence of Antiblackness in Ireland

Australian Journal of Social Issues, EarlyView.
ABSTRACT This paper positions Ireland as a critical site for examining the insistence of blackness and an antiblackness created and sustained through Irish ethnonationalist imaginaries and exclusionary processes. Drawing on connected sociologies and Irish Black Studies, this enquiry argues that antiblackness in Ireland operates as a generational force,
Philomena Mullen
wiley   +1 more source