Results 241 to 250 of about 3,322,214 (305)

Exploring Intraoperative Cognitive Biases in Cardiac Surgery Teams. [PDF]

Appl Hum Factors Ergon Conf
Dias RD, Yule SJ, Harari R, Zenati MA.
europepmc   +1 more source

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

COVID-19-Associated Cognitive Biases on Pneumonia Differential Diagnosis. [PDF]

Cureus
Cruz P, Meireles AM, Santos M, Rodrigues MR.   +3 more
europepmc   +1 more source

Nationwide Real‐World Modeling of Surgical Outcomes in Elderly Patients: Incorporating Geriatric‐Specific Risk Factors Into Prediction of Mortality and Morbidity

Annals of Gastroenterological Surgery, EarlyView.
A reliable and effective risk prediction model for mortality and morbidity in elderly patients undergoing gastroenterological surgeries was developed and validated. Geriatric‐specific risk factors, including the newly added variables in the NCD registry, along with age, were identified as significant contributors to the model. ABSTRACT Aim As the aging
Naoya Sato, Hiraku Kumamaru, Mitsukazu Gotoh, Yoshihiro Kakeji, Yuko Kitagawa, Yasuyuki Seto, Hiromi Rakugi, Masahiro Akishita, Kazue Nakajima, Arata Takahashi, Hiroaki Miyata, Shigeru Marubashi   +11 more
wiley   +1 more source

Analysis of coping capacities and cognitive biases of novice drivers-A questionnaire-based study. [PDF]

PLoS One
Xiang W, Zhang Y, Pan X, Liu X, Xu G.
europepmc   +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

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +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

Mapping cognitive biases in multidisciplinary team (MDT) decision-making for cancer care in Scotland: a cognitive ethnography study protocol. [PDF]

BMJ Open
Dharanikota H, Wigmore SJ, Skipworth R, Yule S.   +3 more
europepmc   +1 more source

Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings

Advanced Intelligent Systems, EarlyView.
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationary. A Minimum Distance to Mean classifier on covariance manifolds uses geodesic distances to outperform convolutional neural networks while reducing ...
Arnau Marin‐Llobet, Sergio Sánchez‐Manso, Arnau Manasanch, Lluc Tresserras, Xinhe Zhang, Yining Hua, Hao Zhao, Melody Torao‐Angosto, Maria V Sanchez‐Vives, Leonardo Dalla Porta   +9 more
wiley   +1 more source