AIMC Topic: Machine Learning

Clear Filters Showing 191 to 200 of 31144 articles

Towards real-world monitoring scenarios: An improved point prediction method for crowd counting based on contrastive learning.

PloS one Jul 2, 2025
In open environments, complex and variable backgrounds and dense multi-scale targets are two key challenges for crowd counting. Due to the reliance on supervised learning with labeled data, current methods struggle to adapt to crowd detection in comp...
Crowding Humans Neural Networks, Computer Machine Learning Algorithms
View on PubMed DOI

Particle swarm optimization-based NLP methods for optimizing automatic document classification and retrieval.

PloS one Jul 2, 2025
Text classification plays an essential role in natural language processing and is commonly used in tasks like categorizing news, sentiment analysis, and retrieving relevant information. [0pc][-9pc]Please check and confirm the inserted city and countr...
Humans Particle Swarm Optimization Algorithms Natural Language Processing Deep Learning Machine Learning Information Storage and Retrieval
View on PubMed DOI

Educational improvement through machine learning: Strategic models for better PISA scores.

PloS one Jul 2, 2025
In this study, in addition to traditional variables such as economic wealth or the number of books read, on which many studies have already been conducted, variables that are thought to influence student achievement and better predict success are ide...
Humans Machine Learning Students Educational Measurement Reading Female Male
View on PubMed DOI

Iron metabolism and preeclampsia: new insights from bioinformatics analysis.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians Jul 1, 2025
OBJECTIVE: Preeclampsia (PE) is a multifactorial systemic pregnancy disease, in which iron metabolism and ferroptosis play significant roles during its pathogenesis. The diagnosis and prevention of PE remain urgent clinical issues that need to be add...
Humans Machine Learning Pregnancy Computational Biology Ferroptosis Iron Female Gene Expression Profiling Pre-Eclampsia
View on PubMed DOI

MoveMentor-examining the effectiveness of a machine learning and app-based digital assistant to increase physical activity in adults: protocol for a randomised controlled trial.

Trials Jul 1, 2025
BACKGROUND: Physical inactivity is prevalent, leading to a high burden of disease and large healthcare costs. Thus, there is a need for affordable, effective and scalable interventions. However, interventions that are affordable and scalable are bese...
Mobile Applications Health Promotion Adult Humans Exercise Randomized Controlled Trials as Topic Machine Learning
View on PubMed DOI

Mapping the EORTC QLQ-C30 and QLQ-LC13 to the SF-6D utility index in patients with lung cancer using machine learning and traditional regression methods.

Health and quality of life outcomes Jul 1, 2025
BACKGROUND: Preference-based measures of health-related quality of life (HRQoL), such as the Short Form Six-Dimension (SF-6D) is essential for health economic evaluations. However, these measures are rarely included in clinical trials for lung cancer...
Lung Neoplasms Aged Humans Regression Analysis Adult China Machine Learning Middle Aged Male Surveys and Questionnaires Algorithms Quality of Life Psychometrics Female
View on PubMed DOI

Nonlinear association between visceral fat metabolism score and heart failure: insights from LightGBM modeling and SHAP-Driven feature interpretation in NHANES.

BMC medical informatics and decision making Jul 1, 2025
OBJECTIVE: Using 2005-2018 NHANES data, this study examined the association between the visceral fat metabolism score (METS-VF) and heart failure (HF) prevalence in U.S. adults, leveraging machine learning (LightGBM/XGBoost) and SHAP for classficatio...
Aged Adult Middle Aged Nutrition Surveys Male Humans Machine Learning Female Intra-Abdominal Fat Boosting Machine Learning Algorithms United States Heart Failure
View on PubMed DOI

Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit.

BMC medical informatics and decision making Jul 1, 2025
BACKGROUND: Determining extubation readiness in pediatric intensive care units (PICU) is challenging. We used expert-augmented machine learning (EAML), a method that combines machine learning with human expert knowledge, to predict successful extubat...
Intensive Care Units, Pediatric Airway Extubation Child, Preschool Machine Learning Child Electronic Health Records Male Infant Female Humans
View on PubMed DOI

GraphGIM: rethinking molecular graph contrastive learning via geometry image modeling.

BMC biology Jul 1, 2025
BACKGROUND: Learning molecular representations is crucial for accurate drug discovery. Using graphs to represent molecules is a popular solution, and many researchers have used contrastive learning to improve the generalization of molecular graph rep...
Drug Discovery Machine Learning
View on PubMed DOI

Prediction of recurrence after surgery for pituitary adenoma using machine learning- based models: systematic review and meta-analysis.

BMC endocrine disorders Jul 1, 2025
BACKGROUND: Predicting pituitary adenoma (PA) recurrence after surgical resection is critical for guiding clinical decision-making, and machine learning (ML) based models show great promise in improving the accuracy of these predictions. These models...
Adenoma Neoplasm Recurrence, Local Humans Prognosis Pituitary Neoplasms Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals