AIMC Topic: Machine Learning

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Knowledge-aware contrastive heterogeneous molecular graph learning.

PLoS computational biology
Molecular representation learning is pivotal in predicting molecular properties and advancing drug design. Traditional methodologies, which predominantly rely on homogeneous graph encoding, are limited by their inability to integrate external knowled...

The role of the sacroiliac joint in sex estimation: Analysis of morphometry and variation types using machine learning techniques.

Legal medicine (Tokyo, Japan)
This study aimed to evaluate the potential of machine learning algorithms in sex estimation by going beyond the traditional two-dimensional (2D) measurements of the pelvic bone, predominantly preferred in sex prediction, by including measurement data...

The long journey of artificial intelligence in medicine: an overview.

Clinical and experimental rheumatology
Artificial intelligence (AI) has its roots in the history of philosophy and of applied mathematics of the 17th, 18th and 19th centuries. Throughout the 20th century, significant advancements in mathematics and computer science laid the groundwork for...

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

Saudi medical journal
OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machine learning predictive model using a large dataset, considering sociodemographic, lifestyle, and clinical factors.

Enhancing mechanical ventilator reliability through machine learning based predictive maintenance.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundWith the advancement of Artificial Intelligence (AI), clinical engineering has witnessed transformative opportunities, enabling predictive maintenance of medical devices, optimization of healthcare workflows, and personalized patient care. ...

Advancing promiscuous aggregating inhibitor analysis with intelligent machine learning classification.

Briefings in bioinformatics
Small molecules have been playing a crucial role in drug discovery; however, some exhibit nonspecific inhibitory effects during hit screening due to the formation of colloidal aggregators. Such false positives often lead to significant research costs...

Machine Learning Models for Predicting Pediatric Hospitalizations Due to Air Pollution and Humidity: A Retrospective Study.

Pediatric pulmonology
BACKGROUND: Exposure to air pollution and meteorological conditions, such as humidity, has been linked to adverse respiratory health outcomes in children. This study aims to develop predictive models for pediatric hospitalizations based on both envir...

Identification of Novel Diagnostic Markers for Atherosclerosis Using Machine-Learning Algorithms.

Journal of the College of Physicians and Surgeons--Pakistan : JCPSP
OBJECTIVE: To outline immune-cell infiltration and identify diagnostic genes for atherosclerosis (AS) to better understand the potential molecular processes involved in AS development.

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients after continuous-flow left ventricular assist device (CF-LVAD) implantation. Abnormalities in mitochondrial oxidative phosphorylation (OxPhos) have been ...

Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study.

European journal of neurology
BACKGROUND: Postural instability and gait difficulties are key symptoms of Parkinson's disease (PD), elevating the risk of falls substantially. Falls afflict 35% to 90% of PD patients, representing a major challenge in managing the condition. Accurat...