AIMC Topic: Machine Learning

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Machine learning based finite element analysis for personalized prediction of pressure injury risk in patients with spinal cord injury.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Patients with spinal cord injury (SCI), are prone to pressure injury (PI) in the soft tissues of buttocks. Early prediction of PI holds the potential to reduce the occurrence and progression of PI. This study proposes a mach...

Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations.

CPT: pharmacometrics & systems pharmacology
A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as they do not ...

Enhanced EEG-based cognitive workload detection using RADWT and machine learning.

Neuroscience
Understanding cognitive workload improves learning performance and provides insights into human cognitive processes. Estimating cognitive workload finds practical applications in adaptive learning systems, brain-computer interfaces, and cognitive mon...

A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.

Epidemics
Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource allocation and public health preparedness. State-of-the-art machine learning methods are a promising approach to produce such forecasts, but they requir...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

American journal of veterinary research
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.

Application of artificial intelligence and machine learning in bovine respiratory disease prevention, diagnosis, and classification.

American journal of veterinary research
Bovine respiratory disease (BRD) is the leading infectious disease in cattle, resulting in significant economic losses and welfare concerns in beef and dairy production systems. Traditional diagnostic methods for BRD typically rely on clinical observ...

Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.

Journal of natural products
The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. Th...

Predicting and Explaining Yields with Machine Learning for Carboxylated Azoles and Beyond.

Journal of chemical information and modeling
Carbon dioxide (CO) can be transformed into valuable chemical building blocks, including C2-carboxylated 1,3-azoles, which have potential applications in pharmaceuticals, cosmetics, and pesticides. However, only a small fraction of the millions of av...

Development and Validation of a Machine Learning Algorithm for Predicting Diabetes Retinopathy in Patients With Type 2 Diabetes: Algorithm Development Study.

JMIR medical informatics
BACKGROUND: Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. Machine learning (ML) systems can enhance DR in community-based screening. However, predictive power models for usability and performance are still being d...

Nutritional intake of micronutrient and macronutrient and type 2 diabetes: machine learning schemes.

Journal of health, population, and nutrition
BACKGROUND: Diabetes mellitus, an endocrine system disease, is a common disease involving many patients worldwide. Many studies are performed to evaluate the correlation between micronutrients/macronutrients on diabetes but few of them have a high st...