Results 181 to 190 of about 803,275 (234)

Preoperative FIB‐4 Index as a Potential Factor Associated With Severe Postoperative Complications and Endogenous Organ Failure After Hepatectomy for Hepatocellular Carcinoma

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This study demonstrates that a preoperative FIB‐4 index ≥ 5.0 independently predicts severe complications and endogenous organ failure (EOF) following hepatectomy for hepatocellular carcinoma. By capturing structural liver fragility and systemic vulnerability, the FIB‐4 index enhances surgical risk stratification beyond traditional functional markers ...
Masanori Nakamura   +9 more
wiley   +1 more source

Mac‐2 Binding Protein Glycosylation Isomer (M2BPGi)–Based Risk Stratification Refined by Tumor Metabolic Activity in Hepatocellular Carcinoma

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
M2BPGi reflects background liver fibrosis and hepatic functional impairment. PET SUVmax reflects tumor metabolic aggressiveness. Their combination identifies a dual‐high subgroup with the poorest recurrence‐free and overall survival. ABSTRACT Aim To evaluate the prognostic significance of preoperative Mac‐2 binding protein glycosylation isomer (M2BPGi)
Kojiro Shirabe   +8 more
wiley   +1 more source

Biological Resectability in Colorectal Liver Metastases: A Nomogram‐Based Continuous Risk Model to Define Borderline Disease

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
KRAS mutation demonstrated a prognostic impact according to primary tumor sidedness, independent of tumor morphology, in patients undergoing hepatectomy for colorectal liver metastases. A nomogram integrating biological and clinicopathological factors was developed to provide continuous biological risk assessment.
Yuzo Umeda   +9 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia   +1 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova   +4 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

open access: yesAdvanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed   +15 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

open access: yesAdvanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha   +2 more
wiley   +1 more source

Behaviorally Adaptive and Inclusive Advanced Driver‐Assistance Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
Advanced driver‐assistance systems (ADASs) are mapped as evolving human‐centered, adaptive technologies linking sensing, driver monitoring, AR/HUD interfaces, patents, regulation, and inclusive design. The review identifies gaps in real‐world evidence, diverse‐driver validation, gaze metrics, and governance, outlining a roadmap for safer, behaviorally ...
Jana Skirnewskaja   +2 more
wiley   +1 more source

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