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Predicting antiretroviral therapy adherence status of adult HIV-positive patients using machine-learning Northwest, Ethiopia, 2025.

BMC medical informatics and decision making
BACKGROUND: Adherence with Anti-Retroviral Therapy (ART) reduces viral load, as well as HIV-related morbidity and mortality. Despite the expanded availability of ART, non-adherence remains a series problem, leads increased viral load, a decline CD4 c...

Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome.

BMC microbiology
Hyperuricemia (HUA) and gout result from imbalances in uric acid metabolism and are closely associated with the gut microbiota. Advanced analytical methods facilitate the exploration of microbiota complexity. In this study, 16S rRNA sequencing data f...

How EEG preprocessing shapes decoding performance.

Communications biology
Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classification performance remains poorly understood. To address this gap, we analyzed seven experiments with 40 participants drawn from the public ERP CORE d...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Scientific reports
Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracerebral hemorrhage. We aimed to develop a risk assessment model to predict the risk of lower extremity DVT during hospitalization in patients with spontan...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Scientific reports
Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drivers of this damage remain unclear. This study explored the dynamics of inflammatory, fibrotic, and endothelial biomarkers in hospitalized COVID-19 pati...

Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning.

Scientific reports
Driver drowsiness is a critical issue in transportation systems and a leading cause of traffic accidents. Common factors contributing to accidents include intoxicated driving, fatigue, and sleep deprivation. Drowsiness significantly impairs a driver'...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

Nature communications
While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence ...

Theory-based chatbot for promoting colorectal cancer screening in a community setting in Hong Kong: study protocol of a randomised controlled trial.

BMJ open
BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality worldwide. Despite the organised CRC screening programme, the uptake rate of the population-based CRC screening was still low. Thus, ...