AIMC Topic: Machine Learning

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Improving genetic variant identification for quantitative traits using ensemble learning-based approaches.

BMC genomics
BACKGROUND: Genome-wide association studies (GWAS) are rapidly advancing due to the improved resolution and completeness provided by Telomere-to-Telomere (T2T) and pangenome assemblies. While recent advancements in GWAS methods have primarily focused...

Lung cancer detection with machine learning classifiers with multi-attribute decision-making system and deep learning model.

Scientific reports
Diseases of the airways and the other parts of the lung cause chronic respiratory diseases. The major cause of lung disease is tobacco smoke, along with risk factors such as dust, air pollution, chemicals, and frequent lower respiratory infections du...

Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.

Scientific reports
Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience extubation failure and reintubation. The aim of this study was to establish an extubation prediction model using explainable machine learning and identif...

Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.

Scientific reports
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxygenated blood to the heart, get occluded due to plaque deposits on their inner walls. The most critic...

Zebrafish identification with deep CNN and ViT architectures using a rolling training window.

Scientific reports
Zebrafish are widely used in vertebrate studies, yet minimally invasive individual tracking and identification in the lab setting remain challenging due to complex and time-variable conditions. Advancements in machine learning, particularly neural ne...

Artificial intelligence for weight estimation in paediatric emergency care.

BMJ paediatrics open
OBJECTIVE: To develop and validate a paediatric weight estimation model adapted to the characteristics of the Spanish population as an alternative to currently extended methods.

Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.

JMIR medical informatics
BACKGROUND: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. ...

Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.

Aging clinical and experimental research
BACKGROUND: Early prediction of progression in dementia is of major importance for providing patients with adequate clinical care, with considerable impact on the organization of the whole healthcare system.

Development of a machine learning-based predictive model for maxillary sinus cysts and exploration of clustering patterns.

Head & face medicine
BACKGROUND AND OBJECTIVE: There are still many controversies about the factors influencing maxillary sinus cysts and their clinical management. This study aims to construct a prediction model of maxillary sinus cyst and explore its clustering pattern...

Development of hybrid robust model based on computational modeling and machine learning for analysis of drug sorption onto porous adsorbents.

Scientific reports
This study investigates the utilization of three regression models, i.e., Kernel Ridge Regression (KRR), nu-Support Vector Regression ([Formula: see text]-SVR), and Polynomial Regression (PR) for the purpose of forecasting the concentration (C) of a ...