Results 161 to 170 of about 1,711,623 (251)

Interaction Between Operator and Assistant Certification Is Associated With Local Recurrence After Laparoscopic Rectal Cancer Surgery: An Ancillary Analysis of the EnSSURE Study

Annals of Gastroenterological Surgery, EarlyView.
A significant synergistic interaction between operator and assistant certification was associated with a lower risk of local recurrence after laparoscopic rectal cancer surgery. Patients treated by both ESSQS‐qualified operators and assistants had the lowest risk of local recurrence, whereas a single qualification alone was not associated with a ...
Yusuke Sakimura, Hiroyuki Bando, Koya Hida, Tatsunari Fukuoka, Tohru Funakoshi, Fuminori Teraishi, Kay Uehara, Yuji Inoue, Nobuaki Suzuki, Nobuki Ichikawa, Hiroaki Iijima, Akinobu Taketomi, Yoshiharu Sakai, Takeshi Naitoh, Ichiro Takemasa, the EnSSURE study group collaboratives within the Japan Society of Laparoscopic Colorectal Surgery, Akinobu Furutani, Akiyoshi Kanazawa, Akiyoshi Noda, Atsushi Ishibe, Chikayoshi Tani, Daisuke Yamamoto, Fumihiko Fujita, Fumio Ishida, Fumitaka Asahara, Heita Ozawa, Hideaki Karasawa, Hideki Osawa, Hiroaki Nagano, Hiroaki Takeshita, Hirofumi Ota, Hirokazu Suwa, Hiroki Ochiai, Hiroomi Ogawa, Hiroshi Saeki, Hirotoshi Hasegawa, Hisanaga Horie, Hisashi Nagahara, Jun Watanabe, Kaori Hayashibara, Kazuhiro Takehara, Ken Kojo, Ken Okamoto, Kenichiro Saito, Koji Ikeda, Koji Munakata, Koki Otsuka, Koki Goto, Kunihiko Nagakari, Mamoru Uemura, Manabu Shimomura, Manabu Shiozawa, Manabu Takata, Manabu Yamamoto, Masaaki Ito, Masafumi Inomata, Masahiko Watanabe, Masakatsu Numata, Masashi Miguchi, Masatsune Shibutani, Mayumi Ozawa, Mitsuhisa Takatsuki, Naoya Aisu, Naruhiko Sawada, Ryo Ikeshima, Ryo Inada, Ryuichi Oshima, Satoshi Maruyama, Shigehiro Kojima, Shigeki Yamaguchi, Shigenori Homma, Shiki Fujino, Shinichiro Mori, Shinobu Ohnuma, Sho Takeda, Shota Aoyama, Shuji Saito, Shunpei Mukai, Shusaku Takahashi, Takahiro Sasaki, Takahiro Yamanashi, Takeru Matsuda, Takuya Miura, Tatsunori Ono, Tatsuya Kinjo, Tatsuya Shonaka, Teni Godai, Tomohiro Adachi, Tomohiro Yamaguchi, Tomohisa Furuhata, Tomonori Akagi, Toshimoto Kimura, Toshisada Aiba, Toshiya Nagasaki, Toshiyoshi Fujiwara, Tsukasa Shimamura, Tsunekazu Mizushima, Yasuhito Iseki, Yasuo Sumi, Yasushi Rino, Yasuyuki Kamada, Yohei Kurose, Yoshiaki Kita, Yoshihiro Kakeji, Yoshihiro Takashima, Yoshihito Ide, Yoshinori Munemoto, Yoshito Akagi, Yoshiyuki Ishii, Yuki Kiyozumi, Yukihito Kokuba, Yukitoshi Todate, Yusuke Sakimura, Yusuke Shimodaira, Yusuke Suwa   +114 more
wiley   +1 more source

Workplace Harassment and Consideration of Leaving Surgical Practice: A Nationwide Survey by the Japanese Society of Gastroenterological Surgery

Annals of Gastroenterological Surgery, EarlyView.
In this nationwide survey of 1967 members of the Japanese Society of Gastroenterological Surgery, 66% reported experiencing workplace harassment, and 56% of those affected had considered leaving surgical practice. These findings highlight the need for sustained, society‐wide efforts to prevent harassment and foster respectful and psychologically safe ...
Keisuke Kurimoto, Tsutomu Fujii, Yoshihiro Shirai, Atsuro Fujinaga, Masayuki Fukumoto, Sonoko Ishida, Koya Hida, Chie Tanaka, Tsunekazu Mizushima, Sachiyo Nomura, Ken Shirabe   +10 more
wiley   +1 more source

AI Powered Biobanks From Static Archives to Dynamic Discovery Engines

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin, Yutian Feng, Wenrui Ma, Yuxin Su, Li Min, Juan Liu   +5 more
wiley   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

Examining Educators' Understanding and Application of Learnings From an Online Brain Injury Professional Development Module-TeachABI. [PDF]

Child Care Health Dev
Muscat CC, Marshall SA, Irvin A, Hickling A, Simic T, Broad K, Scratch SE.   +6 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Moral injury and burnout among saudi educators under vision 2030: An interpretative phenomenological study of systemic ethical tensions. [PDF]

PLoS One
Mansory M.
europepmc   +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

Recommendations for Training Faculty in Generative AI Use: Crafting Higher-Order Application Exercises in Team-Based Learning. [PDF]

Clin Teach
Dalmeida D, Gomaa N, Prabhakar E.
europepmc   +1 more source