Results 141 to 150 of about 91,980 (255)

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

Three little pigs and one big bad wolf: The parable of data sharing in epidemiology. [PDF]

Glob Epidemiol
Burstyn I.
europepmc   +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

Prevalence of MSI‐H/dMMR Colorectal Cancer in Japan: Data From the Clinical Study Group of the University of Osaka‐Colorectal Registry

Annals of Gastroenterological Surgery, EarlyView.
Using a multicenter Japanese colorectal cancer cohort from 25 institutions, we analyzed 1464 patients across all disease stages and tumor locations to determine the prevalence and clinicopathological features of MSI‐H/dMMR colorectal cancer. MSI‐H/dMMR tumors accounted for 9.4% of cases overall, were present in 22% of right‐sided colon cancers, and ...
Yoshihiro Morimoto, Mamoru Uemura, Yoshinori Kagawa, Hidekazu Takahashi, Masayuki Hiraki, Yozo Suzuki, Shinichi Yoshioka, Mitsuyoshi Tei, Shu Okamura, Yukako Mokutani, Atsushi Naito, Shinji Tokuyama, Takamichi Komori, Akinobu Yasuyama, Genta Sawada, Yujiro Fujie, Shinya Yamashita, Naotsugu Haraguchi, Yusuke Matsuura, Chu Matsuda, Yoshinao Chinen, Tatsushi Shingai, Katsuki Danno, Nobuo Tanaka, Kazuya Sakata, Kohei Murata, Yuichiro Doki, Hidetoshi Eguchi   +27 more
wiley   +1 more source

Diagnostic test accuracy meta-analysis of transcranial motor evoked potential monitoring for the prediction of postoperative neurological deficits in ossification of the posterior longitudinal ligament surgery. [PDF]

Clin Neurophysiol Pract
Velur Prasuna L, Vibha V, Marvin G.
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Comparison of different proxy approaches to determine the need for specialized palliative care in patients with incurable cancer. [PDF]

BMC Palliat Care
Reichel N, Heckel M, Gahr S, Ostgathe C.
europepmc   +1 more source

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

Advanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong, Lejia Wang, Tianqing Zhu, Keith Butler, Sichao Li   +4 more
wiley   +1 more source

Comprehensive pharmacovigilance assessment of pairwise drug-drug interactions and acute pancreatitis in the FDA adverse event reporting system: focus on incretin-based drugs. [PDF]

Front Drug Saf Regul
Kazume I, Onda K, Tanaka S, Yokokawa T, Suzuki K.   +4 more
europepmc   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source