Results 281 to 290 of about 1,212,962 (363)

Significance of Neoadjuvant S‐1‐Based Chemotherapy for Older Patients With Locally Advanced Gastric Cancer

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Neoadjuvant chemotherapy (NAC) has been extensively developed for locally advanced gastric cancer (GC). In Asia, S‐1‐based regimens, such as docetaxel, oxaliplatin, and S‐1 (DOS) and S‐1 and oxaliplatin (SOX), are expected to become the standard of care.
Kota Kawabata   +9 more
wiley   +1 more source

Endoscopic Submucosal Dissection Versus Laparoscopic and Endoscopic Cooperative Surgery for Superficial Duodenal Epithelial Tumors: A Multicenter Retrospective Study

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aims This study aimed to compare the clinicopathological features and short‐term outcomes of endoscopic submucosal dissection (ESD) and laparoscopic and endoscopic cooperative surgery (LECS) for superficial duodenal epithelial tumors (SDETs) and investigate the risk factors for severe adverse events (AEs).
Takuo Takehana   +20 more
wiley   +1 more source

Interpretable Active Learning Identifies Iron‐Doped Carbon Dots With High Photothermal Conversion Efficiency for Antitumor Synergistic Therapy

open access: yesAggregate, EarlyView.
On the basis of active learning strategy, we propose an equivalent value—SHapley Additive exPlanations equivalent value—to optimize carbon dots’ photothermal conversion efficiency. Within four iterations, iron‐doped carbon dots are synthesized with the efficiency exceeding 78.7%.
Tianliang Li   +12 more
wiley   +1 more source

Myths About Intimate Partner Violence Against Women in Becoming a Professional: Influence of Gender and Degree in College Students. [PDF]

open access: yesBehav Sci (Basel)
Rebollo-Catalan A   +4 more
europepmc   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai   +8 more
wiley   +1 more source

Enhancing Spinal Metastasis Detection and Feature Evaluation on Computed Tomography Scans Using Deep‐Learning Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
A deep‐learning system (DLS) is developed for the automatic detection of spinal metastases and the evaluation of associated features using computed tomography imaging. A multireader, multicase analysis and a prospective multicenter cohort study are conducted to evaluate the diagnostic performance.
Zhiyu Wang   +16 more
wiley   +1 more source

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