AIMC Topic:
Middle Aged
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Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.
Journal of cardiovascular computed tomography
Feb 4, 2025
BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, using features from CTCS images, we developed a novel machine learning model to predict obstructive coro...
Coronary Vessels
Vascular Calcification
Computed Tomography Angiography
Pericardium
Epicardial Adipose Tissue
Adipose Tissue
Predictive Value of Tests
Coronary Angiography
Coronary Artery Disease
Prognosis
Male
Middle Aged
Risk Assessment
Female
Severity of Illness Index
Reproducibility of Results
Risk Factors
Aged
Humans
Machine Learning
Decision Support Techniques
The external validity of machine learning-based prediction scores from hematological parameters of COVID-19: A study using hospital records from Brazil, Italy, and Western Europe.
PloS one
Feb 4, 2025
The unprecedented worldwide pandemic caused by COVID-19 has motivated several research groups to develop machine-learning based approaches that aim to automate the diagnosis or screening of COVID-19, in large-scale. The gold standard for COVID-19 det...
Automated contouring for breast cancer radiotherapy in the isocentric lateral decubitus position: a neural network-based solution for enhanced precision and efficiency.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Feb 3, 2025
BACKGROUND: Adjuvant radiotherapy is essential for reducing local recurrence and improving survival in breast cancer patients, but it carries a risk of ischemic cardiac toxicity, which increases with heart exposure. The isocentric lateral decubitus p...
A machine learning model using clinical notes to estimate PHQ-9 symptom severity scores in depressed patients.
Journal of affective disorders
Feb 3, 2025
BACKGROUND: Lack of widespread use of the Patient Health Questionnaire 9-item (PHQ-9) in clinical practice inhibits measurement of treatment follow-up for patients with major depressive disorder (MDD). This study developed, validated and applied a ma...
Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.
Academic radiology
Feb 3, 2025
RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur attenuation values and radiomics features at routine CT to predict hip fragility fracture using machine learning methods.
Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study.
The Lancet. Digital health
Feb 3, 2025
BACKGROUND: Emerging evidence suggests that artificial intelligence (AI) can increase cancer detection in mammography screening while reducing screen-reading workload, but further understanding of the clinical impact is needed.
Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.
Journal of the American Heart Association
Feb 3, 2025
BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion and screening tools not being easily accessible such as echocardiography. A new readily available scre...
Clinician Experiences With Ambient Scribe Technology to Assist With Documentation Burden and Efficiency.
JAMA network open
Feb 3, 2025
IMPORTANCE: Timely evaluation of ambient scribing technology is warranted to assess whether this technology can lessen the burden of clinical documentation on clinicians.
Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.
BMC medical informatics and decision making
Feb 3, 2025
BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and intervention in risk populations...
Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models.
BMC medical informatics and decision making
Feb 3, 2025
INTRODUCTION: Renal transplantation is a critical treatment for end-stage renal disease, but graft failure remains a significant concern. Accurate prediction of graft survival is crucial to identify high-risk patients. This study aimed to develop pro...
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