Results 171 to 180 of about 544,701 (235)

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

Educational Impact of Artificial Intelligence‐Navigation Surgery on Anatomical Landmark Recognition in Medical Students

Annals of Gastroenterological Surgery, EarlyView.
This study evaluated the educational impact of artificial intelligence (AI)‐navigation surgery that provides real‐time anatomical landmark recognition during laparoscopic cholecystectomy for medical students. Thirty students were randomized into surgeon‐guided, self‐learning, and AI‐learning groups, and their performance was assessed using Dice ...
Shigeo Ninomiya, Yusuke Matsunobu, Tabito Oyama, Hiroomi Takayama, Takashi Masuda, Teijiro Hirashita, Yuichi Endo, Tatsushi Tokuyasu, Masafumi Inomata   +8 more
wiley   +1 more source

Annual Report of the 2022 National Clinical Database: Decade‐Long Trends and Current Status of Gastroenterological Surgery in Japan

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim The National Clinical Database (NCD) of Japan is the largest nationwide registry, covering over 95% of surgeries in the country. This 2022 annual report summarizes the short‐term outcomes of gastroenterological surgeries and discusses trends and insights over the past decade.
Koshi Kumagai, Arata Takahashi, Hideki Ueno, Naoki Hiki, Yoshiki Kajiwara, Tomoki Ebata, Takao Otsuka, Taro Oshikiri, Yoshihiro Kakeji, Takanori Goi, Akio Saiura, Hiroshi Saeki, Chie Tanaka, Masanori Tokunaga, Tsutomu Fujii, Satoru Matsuda, Tsunekazu Mizushima, Hiroyuki Yamamoto, Yuko Kitagawa, Ken Shirabe   +19 more
wiley   +1 more source

Multifactor Risk Stratification for Post‐Transplant Alcohol Relapse Using Abstinence, Psychosocial, and Socioeconomic Factors

Annals of Gastroenterological Surgery, EarlyView.
Alcohol relapse after liver transplantation is difficult to predict using abstinence duration alone. We developed a multifactor model integrating abstinence duration, psychosocial risk (SIPAT), and socioeconomic context (AUC 0.70). This approach may support individualized risk assessment and tailored follow‐up intensity; external validation is needed ...
Ayato Obana, Garren Montgomery, Miho Akabane, Matthew Hamilton, Navdeep Singh, Musab Alebrahim, Austin Schenk, Sylvester Black, Kenneth Washburn, Khalid Mumtaz   +9 more
wiley   +1 more source

Getting real about synthetic data ethics : Are AI ethics principles a good starting point for synthetic data ethics? [PDF]

EMBO Rep
Shanley D, Hogenboom J, Lysen F, Wee L, Lobo Gomes A, Dekker A, Meacham D.   +6 more
europepmc   +1 more source

Survival Outcomes of Gemcitabine–Cisplatin–S‐1 Versus Gemcitabine–Cisplatin in Unresectable Biliary Tract Cancer: A Multicenter Retrospective Study With a Focus on Conversion Surgery

Annals of Gastroenterological Surgery, EarlyView.
In this multicenter retrospective study conducted by the Biliary Tract Club, we compared survival outcomes between gemcitabine–cisplatin–S‐1 (GCS) and gemcitabine–cisplatin (GC) in patients with unresectable biliary tract cancer, with a particular focus on conversion surgery. GCS was associated with longer overall and progression‐free survival compared
Hisashi Kosaka, Masahiko Kinoshita, Satoshi Yasuda, Satoru Kakizaki, Rie Sugimoto, Jun Sakata, Kiyonori Yamai, Takeshi Hatanaka, Yusuke Yamamoto, Toshifumi Sato, Toru Ishikawa, Takanori Morikawa, Jun Hanaoka, Haruki Mori, Hidenori Toyoda, Tsuyoshi Sanuki, Misaki Yokoi, Hiroyuki Shibata, Koji Fukuda, Kazuhito Kawata, Koji Amaya, Takashi Ito, Masaaki Hidaka, Atsushi Naganuma, Keishi Sugimachi, Satoshi Toshiyama, Makoto Yamasaki, Masaki Kaibori   +27 more
wiley   +1 more source

Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context

Agribusiness, EarlyView.
Alexis H. Villacis
wiley   +1 more source

Diagnostic Accuracy of Size‐Based Preoperative CT Assessment for Predicting Lymph Node Metastasis in Colon Cancer: A Systematic Review and Meta‐Analysis

Annals of Gastroenterological Surgery, EarlyView.
Preoperative CT based on lymph node size shows moderate accuracy for detecting nodal metastasis in colon cancer. In this meta‐analysis of 29 studies (5,634 patients), pooled sensitivity and specificity were 0.69 and 0.66. Size‐based CT alone has limited value for clinical decision‐making.
Yuji Takayama, Tomoya Shimizu, Jun Watanabe, Shimpei Ogawa, Yukihide Kanemitsu   +4 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source