The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat qu...
BACKGROUND: To apply machine learning (ML) algorithms to perform multiclass diabetic retinopathy (DR) classification using both clinical data and optical coherence tomography angiography (OCTA).
The screening and design of "green" biochar materials with high adsorption capacity play a pivotal role in promoting the sustainable treatment of Cd(II)-containing wastewater. In this study, six typical machine learning (ML) models, namely Linear Reg...
Journal of pharmaceutical and biomedical analysis
Jun 13, 2024
Hypericum perforatum L. (HPL), also known as St. John's wort, is one of the extensively researched domestically and internationally as a medicinal plant. In this study, non-targeted metabolomics combined with machine learning methods were used to ide...
Computer methods and programs in biomedicine
Jun 13, 2024
BACKGROUND: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is recommended for high-quality cardiopulmonary resuscitation (CPR). This study aimed to investigate a method for non-invasive estimation of CPP using elect...
OBJECTIVE: To develop and validate natural language processing-driven artificial intelligence (AI) models for the diagnosis of lumbar disc herniation (LDH) with L5 and S1 radiculopathy using electronic health records (EHRs).
The value of machine learning capacity in maternal health, and in particular prediction of preeclampsia will only be realised when there are high quality clinical data provided, representative populations included, different health systems and models...
BACKGROUND: Machine learning (ML) is increasingly used to predict the prognosis of numerous diseases. This retrospective analysis aimed to develop a prediction model using ML algorithms and to identify predictors associated with the recurrence of hal...
Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing comple...
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