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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers.
Scientific reports
Aug 9, 2025
This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithm...
Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours.
Scientific reports
Aug 9, 2025
This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT) using digitised Haematoxylin and Eosin stained whole-slide images (WSI). Machine learning (ML) classifiers were developed and tested using 320 scann...
Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.
Scientific reports
Aug 9, 2025
Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of tuberculosis preventive therapy (TPT) remains inadequately understood. Using observational data from 4152 HIV patients in Ethiopia (2005-2024), we appl...
Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1/PD-L1: a retrospective study.
BMC medical informatics and decision making
Aug 8, 2025
BACKGROUND: Anti-programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) immunotherapy has revolutionized cancer treatment. However, it can cause immune-related adverse events, including acute kidney injury (AKI). Such adverse e...
Machine learning based analysis of leucocyte cell population data by Sysmex XN series hematology analyzer for the diagnosis of bacteremia.
Scientific reports
Aug 8, 2025
In clinical practice, early recognition of bacteremia leads to prognostic improvement. Recently, cell population data (CPD) from the Sysmex XN-series hematology analyzer has attracted attention as a new method for the early diagnosis of bacteremia, b...
Exposotypes in psychotic disorders.
Scientific reports
Aug 8, 2025
Psychiatry lags in adopting etiological approaches to diagnosis, prognosis, and outcome prediction compared to the rest of medicine. Etiological factors such as childhood trauma (CHT), substance use (SU), and socioeconomic status (SES) significantly ...
Breast cancer is detectable from peripheral blood using machine learning over T cell receptor repertoires.
NPJ systems biology and applications
Aug 8, 2025
The immune system's defense abilities rely on the diversity of T and B lymphocytes. T Cell Receptors (TCRs) are generated through V(D)J recombination, where distinct genetic elements combine and undergo modifications, creating extensive variability. ...
Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an Artificial Intelligence-Driven Clinical Prediction Model: Protocol from the Coronary Artery Disease Risk Estimation and Early Detection Consortium.
JMIR research protocols
Aug 8, 2025
BACKGROUND: Atherosclerotic cardiovascular disease poses a heavy burden on the population's health and health care costs. Identifying apparently healthy individuals at risk of developing cardiovascular diseases using clinical prediction models raises...
Effects of a Theory- and Evidence-Based, Motivational Interviewing-Oriented Artificial Intelligence Digital Assistant on Vaccine Attitudes: A Randomized Controlled Trial.
Journal of medical Internet research
Aug 8, 2025
BACKGROUND: Attitude-targeted interventions are important approaches for promoting vaccination. Educational approaches alone cannot effectively cultivate positive vaccine attitudes. Artificial intelligence (AI)-driven chatbots and motivational interv...
Attitudes, Perceptions, and Factors Influencing the Adoption of AI in Health Care Among Medical Staff: Nationwide Cross-Sectional Survey Study.
Journal of medical Internet research
Aug 8, 2025
BACKGROUND: Artificial intelligence (AI) has demonstrated transformative potential in the health care field; yet, its clinical adoption faces challenges such as inaccuracy, bias, and data privacy concerns. As the primary operators of AI systems, phys...
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