Results 221 to 230 of about 2,919,066 (271)

Further Detail Concerning the Deep Learning Model for Mortality After Total Gastrectomy

Annals of Gastroenterological Surgery, EarlyView.
Kentaro Goto, Haruku Fujita, Ryohei Onishi, Nobuaki Hoshino, Koya Hida   +4 more
wiley   +1 more source

Management Strategies for Disappearing Colorectal Liver Metastases After Systemic Chemotherapy: Long‐Term Outcomes and Preoperative Prediction of ‘True Complete Response’

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Determining whether to resect disappearing liver metastases (DLMs) after chemotherapy for colorectal liver metastases (CRLMs) remains challenging. Methods Patients who underwent hepatectomy after systemic chemotherapy for initially unresectable CRLMs were reviewed. True complete response (CR) was defined as either resected DLMs with
Taihei Soma, Ryo Ashida, Takeshi Kawakami, Katsuhisa Ohgi, Mihoko Yamada, Shimpei Otsuka, Yoshiyasu Kato, Kentaro Yamazaki, Katsuhiko Uesaka, Teiichi Sugiura   +9 more
wiley   +1 more source

Preoperative Total Iron‐Binding Capacity Is a Novel Surrogate Marker of Short‐ and Long‐Term Outcomes After Liver Resection for Hepatocellular Carcinoma

Annals of Gastroenterological Surgery, EarlyView.
HCC patients with low preoperative TIBC levels experienced significantly more frequent post‐hepatectomy complications. Furthermore, these patients were significantly correlated with worse survival. Preoperative serum TIBC levels may be a novel surrogate marker of postoperative complications and long‐term survival after hepatectomy.
Taishi Yamane, Hiromitsu Hayashi, Daisuke Ogawa, Shotaro Kinoshita, Yuta Shiraishi, Takanobu Yamao, Yuki Kitano, Tatsunori Miyata, Hirohisa Okabe, Masaaki Iwatsuki   +9 more
wiley   +1 more source

Relationship Between the Product of Pre‐Treatment Neutrophil and Monocyte Counts and Clinical Outcomes in Rectal Cancer With Suspected Lateral Lymph Node Metastasis

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim A novel systemic inflammatory response marker, the neutrophil × monocyte value (NM value), has been identified as a negative predictive factor for responses to chemoradiotherapy in rectal cancer. However, the clinical implications of the NM value remain unknown.
Takayoshi Sasaki, Shinya Abe, Hiroaki Nozawa, Kazuhito Sasaki, Koji Murono, Shigenobu Emoto, Yuichiro Yokoyama, Yuzo Nagai, Yuzo Harada, Soichiro Ishihara   +9 more
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

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

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source