Comparison of Machine Learning Models Including Preoperative, Intraoperative, and Postoperative Data and Mortality After Cardiac Surgery
Sign Up to like & getrecommendations! Published in 2022 at "JAMA Network Open"
DOI: 10.1001/jamanetworkopen.2022.37970
Abstract: This prognostic study compares machine learning models that use preoperative, intraoperative, and postoperative data to predict mortality after cardiac surgery. read more here.
Keywords: machine learning; preoperative intraoperative; learning models; postoperative data ... See more keywords
Integrating Nonindividual Patient Features in Machine Learning Models of Hospital-Onset Bacteremia
Sign Up to like & getrecommendations! Published in 2025 at "JAMA Network Open"
DOI: 10.1001/jamanetworkopen.2025.18815
Abstract: Key Points Question Do nonpatient features that summarize patient interactions with other patients and health care workers impact machine learning models for hospital-onset bacteremia? Findings This prognostic study of 52 442 adult patients hospitalized during 2021… read more here.
Keywords: hospital onset; onset bacteremia; learning models; machine learning ... See more keywords
Comparing self-reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models.
Sign Up to like & getrecommendations! Published in 2025 at "Molecular oncology"
DOI: 10.1002/1878-0261.70013
Abstract: While the incidence of endometrial cancer is increasing among all US women, Black women face higher mortality rates. The reasons for this remain unclear. In this study, whole genome differential methylation analysis, along with state‐of‐the‐art… read more here.
Keywords: african ancestry; genetic ancestry; learning models; machine learning ... See more keywords
Machine learning models for classifying coffee fruits detachment force
Sign Up to like & getrecommendations! Published in 2024 at "Agronomy Journal"
DOI: 10.1002/agj2.21633
Abstract: The maturation process of coffee (Coffea arabica) trees exhibits inherent variability, producing fruits at various physiological maturity stages. This variability affects the resistance between the fruit and its peduncle, posing a challenge in mechanized harvesting:… read more here.
Keywords: coffee; learning models; force; machine learning ... See more keywords
Predicting Neoplastic Polyp in Patients With Gallbladder Polyps Using Interpretable Machine Learning Models: Retrospective Cohort Study
Sign Up to like & getrecommendations! Published in 2025 at "Cancer Medicine"
DOI: 10.1002/cam4.70739
Abstract: Gallbladder polyps (GBPs) are increasingly prevalent, with the majority being benign; however, neoplastic polyps carry a risk of malignant transformation, highlighting the importance of accurate differentiation. This study aimed to develop and validate interpretable machine… read more here.
Keywords: gallbladder polyps; learning models; retrospective cohort; machine learning ... See more keywords
Optimizing Deep Learning Models for Luminal and Nonluminal Breast Cancer Classification Using Multidimensional ROI in DCE‐MRI—A Multicenter Study
Sign Up to like & getrecommendations! Published in 2025 at "Cancer Medicine"
DOI: 10.1002/cam4.70931
Abstract: Previous deep learning studies have not explored the synergistic effects of ROI dimensions (2D/2.5D/3D), peritumoral expansion levels (0–8 mm), and segmentation scenarios (ROI only vs. ROI original). Our study aims to evaluate the performance of multidimensional… read more here.
Keywords: deep learning; breast; learning models; dce mri ... See more keywords
SAnDReS 2.0: Development of machine‐learning models to explore the scoring function space
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Computational Chemistry"
DOI: 10.1002/jcc.27449
Abstract: Classical scoring functions may exhibit low accuracy in determining ligand binding affinity for proteins. The availability of both protein–ligand structures and affinity data make it possible to develop machine‐learning models focused on specific protein systems… read more here.
Keywords: scoring function; function space; learning models; machine learning ... See more keywords
Comparing Explanations of Molecular Machine Learning Models Generated with Different Methods for the Calculation of Shapley Values
Sign Up to like & getrecommendations! Published in 2025 at "Molecular Informatics"
DOI: 10.1002/minf.202500067
Abstract: Feature attribution methods from explainable artificial intelligence (XAI) provide explanations of machine learning models by quantifying feature importance for predictions of test instances. While features determining individual predictions have frequently been identified in machine learning… read more here.
Keywords: machine; feature importance; learning models; machine learning ... See more keywords
Machine Learning Models for Predicting Liver Toxicity.
Sign Up to like & getrecommendations! Published in 2022 at "Methods in molecular biology"
DOI: 10.1007/978-1-0716-1960-5_15
Abstract: Liver toxicity is a major adverse drug reaction that accounts for drug failure in clinical trials and withdrawal from the market. Therefore, predicting potential liver toxicity at an early stage in drug discovery is crucial… read more here.
Keywords: learning models; drug; toxicity; liver toxicity ... See more keywords
Hypermetabolic pulmonary lesions detection and diagnosis based on PET/CT imaging and deep learning models
Sign Up to like & getrecommendations! Published in 2025 at "European Journal of Nuclear Medicine and Molecular Imaging"
DOI: 10.1007/s00259-025-07215-0
Abstract: This study aims to develop and evaluate deep learning models for the detection and classification of hypermetabolic lung lesions into four categories: benign, lung cancer, pulmonary lymphoma, and metastasis. These categories are defined by their… read more here.
Keywords: deep learning; detection; learning models; external test ... See more keywords
Cyberbullying detection solutions based on deep learning architectures
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Systems"
DOI: 10.1007/s00530-020-00701-5
Abstract: Cyberbullying is disturbing and troubling online misconduct. It appears in various forms and is usually in a textual format in most social networks. Intelligent systems are necessary for automated detection of these incidents. Some of the… read more here.
Keywords: learning; learning models; deep learning; cyberbullying detection ... See more keywords