AIMC Topic: Machine Learning
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Urea-mediated growth engineering of Au@Ag core-shell nanostructures: an enzymatic detection strategy with machine learning-assisted comparative analysis.
Mikrochimica acta
Jul 29, 2025
A non-invasive, enzyme-based colorimetric biosensor was developed for urea detection in saliva, utilizing a growth-based method with Au@Ag core-shell nanostructures, including CTAB-coated gold nanoparticles (AuNPs) and CTAB-coated gold nanorods with ...
Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study.
Scientific reports
Jul 29, 2025
Primary liver cancer is the sixth most commonly diagnosed cancer globally and the third leading cause of cancer-related deaths. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and microvascular invasion (MVI) is a sign...
Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.
Scientific reports
Jul 29, 2025
The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessment is labor-intensive, requiring the counting of 500-2,000 cells in hotspots. Digital image analysis could streamline this process, yet few comprehensi...
IoT enabled health monitoring system using rider optimization algorithm and joint process estimation.
Scientific reports
Jul 29, 2025
The timely detection of abnormal health conditions is crucial in achieving successful medical intervention and enhancing patient outcomes. Despite advances in health monitoring, existing methods often struggle with achieving high accuracy, sensitivit...
Evidence Based Gait Analysis Interpretation Tools (EB-GAIT) treatment recommendation and outcome prediction models to support decision-making based on clinical gait analysis data.
PloS one
Jul 29, 2025
Clinical gait analysis (CGA) has historically relied on clinician experience and judgment, leading to modest, stagnant, and unpredictable outcomes. This paper introduces Evidence-Based Gait Analysis Interpretation Tools (EB-GAIT), a novel framework l...
Relative importance of socioecological domains to predicting opioid-involved mortality.
PloS one
Jul 29, 2025
BACKGROUND: The opioid crisis in the United States is a complex issue with interconnected factors that lead to opioid misuse and opioid-involved mortality. This study assessed the relative importance of different risk factor domains in predicting fat...
Predicting depressive symptoms through social support: a machine learning approach in military populations.
European journal of psychotraumatology
Jul 28, 2025
Perceived Social support has been consistently shown to reduce depressive symptoms among military personnel. However, limited research has explored how different types of support, emotional, informational, and instrumental, from multiple sources uni...
Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.
BMC medical imaging
Jul 28, 2025
BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer great opportunities to support cancer diagnosis. The inability to interpret the extracted features and model predictions is one of the major issues li...
Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning.
BMC medical informatics and decision making
Jul 28, 2025
INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially in triage, where accurate prioritisation is essential for patient safety and resource utilisation. Building on previous research, this study leverages...
Prediction of early postoperative complications and transfusion risk after lumbar spinal stenosis surgery in geriatric patients: machine learning approach based on comprehensive geriatric assessment.
BMC medical informatics and decision making
Jul 28, 2025
BACKGROUND: Lumbar spinal stenosis is one of the most common surgery-requiring conditions of the spine in the aged population. As elderly patients often present with multiple comorbidities and limited physiological reserve, individualized risk assess...
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