Results 211 to 220 of about 107,685 (262)

Age‐Dependent Prognostic Significance of Preoperative Transthyretin After Curative Resection for Stage I–III Colorectal Cancer

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Preoperative malnutrition and systemic inflammation are established determinants of adverse outcomes in colorectal cancer (CRC). Transthyretin (TTR), a rapid‐turnover hepatic protein, reflects both nutritional and inflammatory status; however, its clinical utility may be influenced by age‐ and sex‐related variability.
Ayane Kawata, Yuji Miyamoto, Hiro Nakamura, Takahiko Akiyama, Kota Arima, Katsuhiro Ogawa, Yukiharu Hiyoshi, Masaaki Iwatsuki   +7 more
wiley   +1 more source

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

Annals 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, Yukiyasu Okamura, Osamu Aramaki, Nao Yoshida, Yusuke Mitsuka, Hayato Abe, Shunsuke Yamagishi, Yasuhiro Okumura, Kyongsun Pak, Shinobu Masuda   +9 more
wiley   +1 more source

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

Annals 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, Toshiharu Mitsuhashi, Tomokazu Fuji, Toru Kojima, Takeshi Koujima, Tatsuo Matsuda, Daisuke Satoh, Masaru Inagaki, Kosei Takagi, Toshiyoshi Fujiwara   +9 more
wiley   +1 more source

Machine learning driven many‐objective moving horizon scheduling optimization

AIChE Journal, EarlyView.
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

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

Advanced 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, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Benchmarking Data‐Driven Control of Octopus‐Inspired Soft Arms in Underwater Environment

Advanced Intelligent Systems, EarlyView.
Underwater soft robots present safe, compliant interaction, yet reproducible control remains scarce. This work presents an open benchmark for octopus‐inspired arms: a smooth, velocity‐diverse data‐collection scheme produces a compact dataset to train a vanilla policy.
Muhammad Sunny Nazeer, Yasmin Tauqeer Ansari, Emanuele Solfiti, Baljinder Singh Bal, Matteo Lo Preti, Barbara Mazzolai, Cecilia Laschi   +6 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source