AIMC Topic: Retrospective Studies
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Beam orientation optimization in IMRT using sparse mixed integer programming and non-convex fluence map optimization.
Physics in medicine and biology
Jul 4, 2025
Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is a complex, non-convex problem traditionally addressed with heuristic methods.This work demonstrates the potential improvement of the proposed BOO, providing a math...
Peripheral HLA-DRCD141 Classical Monocytes Predict Relapse Risk and Worsening in Multiple Sclerosis.
Neurology(R) neuroimmunology & neuroinflammation
Jul 3, 2025
BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the CNS characterized by a heterogeneous disease trajectory, highlighting the need for biomarkers to predict disease activity. Current disease-monitorin...
Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients.
Cardiovascular diabetology
Jul 3, 2025
BACKGROUND: Coronary Heart Disease (CHD) and Non-Alcoholic Fatty Liver Disease (NAFLD) share overlapping pathogenic mechanisms including adipose tissue dysfunction, insulin resistance, and systemic inflammation mediated by adipokines. However, the sp...
Predicting carotid atherosclerosis in latent autoimmune diabetes in adult patients using machine learning models: a retrospective study.
BMC cardiovascular disorders
Jul 3, 2025
BACKGROUND: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of diabetes with autoimmune origins. Patients with LADA are at an elevated risk of developing cardiovascular diseases, including carotid atherosclerosis. While machi...
Explainable artificial intelligence for predicting medical students' performance in comprehensive assessments.
Scientific reports
Jul 3, 2025
Comprehensive medical assessments are critical for evaluating clinical proficiency in medical education; however, these administrations impose significant institutional burdens, financial costs, and psychological strain on students. While Artificial ...
Machine learning algorithms for prediction of cerebrospinal fluid leakage after posterior surgery for thoracic ossification of the ligamentum flavum.
Scientific reports
Jul 3, 2025
To develop and validate a machine-learning (ML) model that pre-operatively predicts cerebrospinal-fluid leakage (CSFL) after posterior decompression for thoracic ossification of the ligamentum flavum (TOLF), and to elucidate the key risk factors driv...
Deep learning-based approach to third molar impaction analysis with clinical classifications.
Scientific reports
Jul 3, 2025
This study developed a deep learning model for the automated detection and classification of impacted third molars using the Pell and Gregory Classification, Winter's Classification, and Pederson Difficulty Index. Panoramic radiographs of patients tr...
Development of a single-center predictive model for conventional in vitro fertilization outcomes excluding total fertilization failure: implications for protocol selection.
Journal of ovarian research
Jul 2, 2025
OBJECTIVES: To develop a multidimensional clinical indicator-based prediction model for identifying high-risk patients with fertilization failure conventional in vitro fertilization (c-IVF) cycles, thereby optimizing therapeutic decision-making.
Integrating CT radiomics and clinical features using machine learning to predict post-COVID pulmonary fibrosis.
Respiratory research
Jul 2, 2025
BACKGROUND: The lack of reliable biomarkers for the early detection and risk stratification of post-COVID-19 pulmonary fibrosis (PCPF) underscores the urgency advanced predictive tools. This study aimed to develop a machine learning-based predictive ...
Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana.
BMC pregnancy and childbirth
Jul 2, 2025
BACKGROUND: Machine learning algorithms may contribute to improving maternal and child health, including determining the suitability of caesarean section (CS) births in low-resource countries. Despite machine learning algorithms offering a more robus...
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