Results 141 to 150 of about 44,463 (307)

Predicting the operational carbon emissions of urban community service units by using a two-stage explainable machine learning method: a case study in Nanjing, China

Journal of Asian Architecture and Building Engineering
Low-carbon community development is fundamental to urban sustainability. With accelerating urbanization, the growing demand for community services which occur in non-residential units (e.g.
Jiashu Zhang, Jingfeng Yuan, Shu Su, Shenghua Zhou, Jianli Hao, Qiushi Fang   +5 more
doaj   +1 more source

Prediction of concentrated drainage water quality in cooling tower by interpretable machine learning model

Gongye shui chuli
Taking the circulating cooling water system of a certain power plant as the research object, an integrated prediction model based on “concentration ratio + influent water quality + effluent water quality” was constructed.
WAN Yongjie, ZHANG Ying, TONG Peng, TIAN Xing, HE Hanhua, CHEN Zhenguo, WANG Xiaojun   +6 more
doaj   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Method of dynamic trust assessment in Zero Trust Architecture based on explainable artificial intelligence

Ìнформаційні технології та компʼютерна інженерія
The transformation of contemporary corporate IT infrastructures has rendered conventional cybersecurity models ineffective, prompting a shift to the Zero Trust Architecture (ZTA); however, its practical implementation is complicated by a rigid reliance ...
A. Palamarchuk
doaj   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Two-Level Ensemble with Four Meta-Features for Diabetes Classification on Clinical Tabular Data

Journal of Applied Informatics and Computing
Diabetes mellitus remains a major global public health challenge due to its increasing prevalence, high risk of chronic complications, and growing burden on healthcare systems.
Farid Ma'ruf, Ifnu Wisma Dwi Prasetya, Ita Aristia Sa’ida   +2 more
doaj   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Machine learning for prediction of histologic chorioamnionitis (stage ≥II) in parturients receiving labor analgesia: a retrospective multicentre cohort study

Frontiers in Medicine
BackgroundHistological chorioamnionitis (HCA) is a serious pregnancy complication, but early diagnosis is challenging, especially in parturients receiving labor analgesia, where identification is even more difficult. Therefore, we developed and validated
Chunping Li, Bo Liu, Liang Ling, Jianping Zhang, Jian Zhang, Fei Jia, Yong Tang   +6 more
doaj   +1 more source

Explanation Multiplicity in SHAP: Characterization and Assessment

CoRR
Post-hoc explanations are widely used to justify, contest, and review automated decisions in high-stakes domains such as lending, employment, and healthcare. Among these methods, SHAP is often treated as providing a reliable account of which features mattered for an individual prediction and is routinely used to support recourse, oversight, and ...
Hyunseung Hwang, Seungeun Lee, Lucas Rosenblatt, Steven Euijong Whang, Julia Stoyanovich   +4 more
openaire   +2 more sources

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source