AIMC Topic: Machine Learning

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Cardiovascular risk assessment enhanced by automated machine learning in a multi-phase study.

Scientific reports
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and current predictors such as lipoprotein (a) [Lp(a)] and risk scores have limitations. Automated machine learning (AutoML) offers the potential to improve CVD risk prediction ...

Adaptive resource aware and privacy preserving federated edge learning framework for real time internet of medical things applications.

Scientific reports
The Internet of Medical Things requires frameworks that ensure secure processing, computational efficiency, and scalability for continuous healthcare data streams. Existing solutions remain limited in their ability to support real-time anomaly detect...

A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region.

Scientific reports
Improving accuracy and timeliness for osteoporosis diagnosis could help prevent fragility fractures, morbidity, and mortality for older individuals. Osteoporosis is an often silent health condition, especially as regards vertebral fractures, and WHO ...

Artificial intelligence coupled to pharmacometrics modelling to tailor malaria and tuberculosis treatment in Africa.

Nature communications
Africa's vast genetic diversity poses challenges for optimising drug treatments in the continent, which is exacerbated by the fact that drug discovery and development efforts have historically been performed outside Africa. This has led to suboptimal...

Automated Video-EEG Analysis in Epilepsy Studies: A Narrative Review of Advances and Challenges.

Journal of medical systems
Video-electroencephalography (vEEG) monitoring is currently the reference standard in the diagnosis of epilepsy. Manual analysis of vEEG recordings is time-consuming and inter-rater agreement is low even when the annotation is done by experienced doc...

Age-specific prevalence and predictors of lifetime suicide attempts using machine learning in Chinese adults: a nationwide multi-centre survey.

Epidemiology and psychiatric sciences
AIMS: The epidemiology and age-specific patterns of lifetime suicide attempts (LSA) in China remain unclear. We aimed to examine age-specific prevalence and predictors of LSA among Chinese adults using machine learning (ML).

A microneedle-based integrated three-electrode system for pesticide detection using machine learning.

The Analyst
Pesticides contribute to enhanced agricultural productivity, yet excessive residues pose significant health risks to humans as they persist even after washing, making their detection in crops critically important. In this study, we employed 3D-printe...

Machine Learning Study of PFAS Intermediate Adsorption on Transition Metals: Scaling Relationships for Environmental Catalyst Design.

Environmental science & technology
Per- and polyfluoroalkyl substances (PFASs), particularly trifluoroacetic acid (TFA), have emerged as global environmental pollutants due to their extreme persistence. Conventional treatment methods are largely ineffective, underscoring the need for ...

An analytical and machine learning approach for total mercury and methylmercury determination in squid: enhancing food safety testing and traceability monitoring systems.

Food chemistry
This study presents the first assessment of total mercury (THg) and methylmercury (MeHg) in squids (Todarodes sagittatus, L.), providing insights into contamination levels and their correlation with the geographical origin. A method based on acidic e...

A machine learning framework for classifying lipids in untargeted metabolomics using mass-to-charge ratios and retention times.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: The identification of unknown metabolites remains a major challenge in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS). This process typically depends on comparing mass spectral or chromatographic data to r...