Results 231 to 240 of about 44,463 (307)

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Prediction of Risk of Unplanned Readmission or Death in Elderly Heart Failure Patients During the Vulnerable Phase: Machine Learning With SHAP Interpretation. [PDF]

FASEB Bioadv
Luo H, Wu Q, Zheng Z, Wang X, Lai N, Li Y, Zheng X, Li Y, Li D, Guo K, Li J.   +10 more
europepmc   +1 more source

A Prediction Model for One‐Year Disability Risk Among Community‐Dwelling Older Adults in China: Integrating Physical, Metabolic, and Psychosocial Factors

Health Care Science, EarlyView.
Based on a prospective cohort of 1003 older adults, we developed and validated a practical disability prediction model integrating physical, metabolic, and psychosocial factors (AUC = 0.716), presented via a user‐friendly nomogram for community use. ABSTRACT Background Disability in older adults, characterized by progressive limitations in performing ...
Yanjun Ma, Chaofan Geng, Zhibin Wang, Yiwei Zhao, Lixin Ma, Pengpeng Ye, Leilei Duan, Guoping Peng, Yi Tang   +8 more
wiley   +1 more source

Interpretable Machine Learning for Predicting Metabolic Syndrome-Kidney Stone Disease Comorbidity: The Role of Dietary Micronutrients. [PDF]

Food Sci Nutr
Wu G, Qin H, Yao J, Liu Y, Zheng J, Wang J, Hao Z, Tao L.   +7 more
europepmc   +1 more source

Machine Learning Methods to Predict the Length of Stay for Acute Stroke: A Scoping Review and Meta‐Analysis

Health Care Science, EarlyView.
Current machine learning models for predicting the length of stay for acute stroke lack clinical utility and reliability. This scoping review highlights areas for improvement to develop more robust, interpretable, generalizable, and clinically actionable models that optimize personalized clinical pathways and support precise decision‐making for stroke ...
Zhenran Xu, Monique F. Kilkenny, Tzu‐Yung Kuo, Jia Rong, Lachlan L. Dalli   +4 more
wiley   +1 more source

Identification of BMI-related high-risk feature combinations for diabetes among young adults with normal baseline fasting plasma glucose using interpretable machine learning: a health check-up cohort study. [PDF]

Front Endocrinol (Lausanne)
Xu Z, Zhang Y, Zhang H.
europepmc   +1 more source

Identifying Venous Insufficiency in Head and Neck Reconstruction Flaps Using Machine Learning and Deep Learning Methods

Head &Neck, EarlyView.
ABSTRACT Background Venous insufficiency is a major cause of flap failure in head and neck reconstruction. AI provides a reliable, convenient solution for early detection. Methods Clinical data and postoperative flap photos of head and neck cancer patients (2018–2024) at our center were retrospectively collected, categorized into normal and venous ...
Yurong He, Jugao Fang, Lizhen Hou, Zufei Li, Shizhi He, Yanming Zhao, Qijia Li, Rongjia Li, Xiaoyu Shi, Jiayi Yang, Qi Zhong   +10 more
wiley   +1 more source

Predicting long-term allograft outcomes in kidney transplant recipients using a machine learning approach: a 5-year retrospective cohort study. [PDF]

Ren Fail
Gao X, Chen J, Wang M, Li Z, Lou X, Chen J.   +5 more
europepmc   +1 more source

Closing the Loop in Precision Oncology: A Digital Twin‐Driven Paradigm for Dynamic Decision‐Making

iMetaMed, EarlyView.
This review introduces the Closed‐Loop Intelligent Oncology System (CIOS), a five‐layer framework integrating digital twins and AI to enable adaptive, data‐driven cancer treatment. By synthesizing advances in multimodal perception, mechanistic simulation, and safe reinforcement learning, CIOS charts a roadmap toward dynamic, personalized oncology ...
Junye Zhu, Mengqi Yang, Chenxi Ouyang, Lin Zhang   +3 more
wiley   +1 more source