Results 211 to 220 of about 150,441 (331)

Development and Validation of an Interpretable Machine Learning Model for Predicting Tumor Recurrence After Microwave Ablation in Small Hepatocellular Carcinoma. [PDF]

J Hepatocell Carcinoma
Ma Y, Zhao L, Zhao Q.
europepmc   +1 more source

Machine learning‐based prediction of large‐for‐gestational‐age neonates in diabetic and non‐diabetic pregnancies

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objective This study determines whether a machine‐learning model integrating sonographic biometry with maternal clinical parameters improves prediction of large‐for‐gestational‐age (LGA) compared with Hadlock's EFW formula. Methods We conducted a retrospective cohort study including all singleton live births at ≥32 gestational weeks at a ...
Ohad Houri, Asaf Romano, Asnat Walfisch, Eran Hadar, Yinon Gilboa, Leor Perl, Nadav Loebl, Ron Unger   +7 more
wiley   +1 more source

Development and validation of a machine learning model for predicting high-risk distant metastatic recurrence in differentiated thyroid cancer. [PDF]

Front Med (Lausanne)
Yang F, Zhang J, Liu T, Zhao Z.
europepmc   +1 more source

Progress of metabolomics‐centric multi‐omics research in medicine

iMetaOmics, EarlyView.
The graphical abstract illustrates a holistic roadmap for metabolomics‐centric multi‐omics integration in medical research. The upper panel depicts the technological transition from traditional bulk analysis to high‐resolution single‐cell and spatial methodologies, specifically addressing inherent challenges such as molecular complexity and dynamic ...
Ziyi Wang, Shiwen Deng, Xiaoxu Wang, Xiao Chang, Na Guo, Peng Chen, Hongjun Yang   +6 more
wiley   +1 more source

Hybrid ML and metaheuristic optimization of slag-fly ash-gypsum modified solidified sludge for construction. [PDF]

Sci Rep
Azarkhosh H, Chen Y, Elias S.
europepmc   +1 more source

Metabolic Signatures and Diagnostic Prediction Models for Coronary Artery Disease and Type 2 Diabetes Mellitus: Insights From an Exploratory Study

iNew Medicine, EarlyView.
Metabolomic & lipidomic analysis reveals metabolic overlap between CAD & T2DM, highlighting 7 key metabolites as potential biomarkers. A predictive model based on these achieves high accuracy, potentially advancing precision medicine & metabolic insights.
Zhihua Wang, Meiming Su, Ying Li, Yapei Li, Shuo Chen, Ting Peng, Hans Strijdom, Jiangang Wang, Jianping Weng, Suowen Xu   +9 more
wiley   +1 more source

Soil classification in the Sudan Savanna using sentinel products and topographic information with machine learning models. [PDF]

Sci Rep
Maung WS, Kenta I, Toru S, Saïdou S, Lamine Z, Nicolas K.   +5 more
europepmc   +1 more source

Interpretable machine learning enables early and accurate detection of drug‐induced liver injury: A multicenter study with real‐world clinical translation

Interdisciplinary Medicine, EarlyView.
This study develops an interpretable gradient‐boosting model that accurately identifies drug‐induced liver injury (DILI) using routine laboratory data. The model explains key clinical features through SHapley Additive exPlanations analysis and detects DILI earlier than expert evaluation, offering a transparent and practical tool for precision ...
Jingyi Ling, Shian Zhang, Jun Lin, Zhengju Xu, Runcheng Xu, Qian Lv, Kaixiang Zhang, Sheng Liu, Jie Guo, Cheng Hua, Yin Jia, Xiaoyu Xu, Kun Qian, Shanrong Liu   +13 more
wiley   +1 more source

Comparative Performance of 3 Analytical Models in Identifying Associated Factors of Pulmonary Dysfunction-Depression Comorbidity: China Health and Retirement Longitudinal Study-Based Nationwide Cross-Sectional Study.

JMIR Med Inform
Cheng Q, Cao Q, Teng W, Dai R, Jia Q, Bai X, Li Q, Wu Y, Huang Y.   +8 more
europepmc   +1 more source

Quantification of Soil Organic Carbon by Shifted-Excitation Raman Difference Spectroscopy with Machine Learning and Common Mode Rejection. [PDF]

Anal Chem
Brown GW, Solomatova NV, Yamaoka NK, Cole C, Prescott P, Kowal MD, Melo L, Larose M, Shokatian S, Grant E.   +9 more
europepmc   +1 more source