AIMC Topic: Machine Learning

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Hierarchical machine learning-based prediction for ultrasonic degradation of organic pollutants using sonocatalysts.

Environmental research
Ultrasound-based advanced oxidation processes (AOPs) are effective for degrading organic pollutants, with hydrogen peroxide (HO) acting as a key intermediate in radical generation and overall degradation efficiency. However, conventional machine lear...

Bacillus subtilis morphology and bentonite colloids govern Eu(III) transport in quartz sand: Mechanisms and machine learning insights.

Journal of hazardous materials
Microorganisms critically regulate radionuclide migration through diverse biological mechanisms. Bacillus subtilis (B. subtilis) exhibits strong adsorption capacity, immobilizing radionuclides and limiting their mobility. By contrast, biological coll...

Beyond unimodal analysis: Multimodal ensemble learning for enhanced assessment of atherosclerotic disease progression.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Atherosclerosis is a leading cardiovascular disease typified by fatty streaks accumulating within arterial walls, culminating in potential plaque ruptures and subsequent strokes. Existing clinical risk scores, such as systematic coronary risk estimat...

Predicting Subcutaneous Antibody Bioavailability Using Ensemble Protein Language Models.

Molecular pharmaceutics
Monoclonal antibodies are pivotal in modern therapeutics, yet predicting their subcutaneous bioavailability remains challenging due to the intricacies of the SC environment and the limitations of traditional experimental models. In this study, we int...

Bridging the predictive divide: A hybrid early warning system for scalable and real-time dengue surveillance in LMICs.

Acta tropica
The global resurgence of dengue presents an ongoing challenge for public health systems, particularly in low- and middle-income countries (LMICs) where conventional early warning systems (EWS) often suffer from reporting delays and under-detection. W...

Machine Learning-Enhanced Calculation of Quantum-Classical Binding Free Energies.

Journal of chemical theory and computation
Binding free energies are key elements in understanding and predicting the strength of protein-drug interactions. While classical free energy simulations yield good results for many purely organic ligands, drugs, including transition metal atoms, oft...

Robust Quantum Reservoir Learning for Molecular Property Prediction.

Journal of chemical information and modeling
Machine learning has been increasingly utilized in the field of biomedical research to accelerate the drug discovery process. In recent years, the emergence of quantum computing has led to the extensive exploration of quantum machine learning algorit...

Development and interpretation of a machine learning risk prediction model for post-stroke depression in a Chinese population.

Scientific reports
Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learning (ML) remains limited. The aim of this study is to develop a superior predictive model based on ML algorithms for PSD in the Chinese population. We r...

Transfer learning driven fake news detection and classification using large language models.

Scientific reports
Today, the problem of using social media to spread false information is not only widespread but also quite serious. The extensive dissemination of fake news, regardless of whether it is produced by human beings or computer programs, has a negative im...

Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study.

Virology journal
Antiretroviral therapy (ART) has transformed HIV from a rapidly progressive and fatal disease to a chronic disease with limited impact on life expectancy. However, people living with HIV(PLWHs) faced high critical illness risk due to the increased pr...