AIMC Topic: Cohort Studies
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Accurate prediction of bleeding risk after coronary artery bypass grafting with dual antiplatelet therapy: A machine learning model vs. the PRECISE-DAPT score.
International journal of cardiology
Dec 22, 2024
BACKGROUND: Dual antiplatelet therapy (DAPT) after coronary artery bypass grafting (CABG), although might be protective for ischemic events, can lead to varying degrees of bleeding, resulting in serious clinical events, including death. This study ai...
Effectiveness of Machine Learning-Based Adjustments to an eHealth Intervention Targeting Mild Alcohol Use.
European addiction research
Dec 20, 2024
INTRODUCTION: This study aimed to evaluate effects of three machine learning based adjustments made to an eHealth intervention for mild alcohol use disorder, regarding (a) early dropout, (b) participation duration, and (c) success in reaching persona...
Development and validation of machine learning models for predicting venous thromboembolism in colorectal cancer patients: A cohort study in China.
International journal of medical informatics
Dec 19, 2024
BACKGROUND: With advancements in healthcare, traditional VTE risk assessment tools are increasingly insufficient to meet the demands of high-quality care, underscoring the need for innovative and specialized assessment methods.
Machine learning analysis of sex and menopausal differences in the gut microbiome in the HELIUS study.
NPJ biofilms and microbiomes
Dec 19, 2024
Sex differences in the gut microbiome have been examined previously, but results are inconsistent, often due to small sample sizes. We investigated sex and menopausal differences in the gut microbiome in a large multi-ethnic population cohort study, ...
XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study.
Arthritis research & therapy
Dec 19, 2024
OBJECTIVE: To use routine demographic and clinical data to develop an interpretable individual-level machine learning (ML) model to diagnose knee osteoarthritis (KOA) and to identify highly ranked features.
Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.
International journal of cardiology
Dec 18, 2024
BACKGROUND: Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and some...
Dual biomarkers CT-based deep learning model incorporating intrathoracic fat for discriminating benign and malignant pulmonary nodules in multi-center cohorts.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Dec 16, 2024
BACKGROUND: Recent studies in the field of lung cancer have emphasized the important role of body composition, particularly fatty tissue, as a prognostic factor. However, there is still a lack of practice in combining fatty tissue to discriminate ben...
Utilizing machine learning approaches to investigate the relationship between cystatin C and serious complications in esophageal cancer patients after esophagectomy.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Dec 16, 2024
BACKGROUND: The purpose of this study is to investigate the relationship between preoperative cystatin C levels and the risk of serious postoperative complications in esophageal cancer (EC) patients, utilizing advanced machine learning (ML) methodolo...
Does machine learning improve prediction accuracy of the Endoscopic Third Ventriculostomy Success Score? A contemporary Hydrocephalus Clinical Research Network cohort study.
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Dec 10, 2024
PURPOSE: This Hydrocephalus Clinical Research Network (HCRN) study had two aims: (1) to compare the predictive performance of the original ETV Success Score (ETVSS) using logistic regression modeling with other newer machine learning models and (2) t...
Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.
Journal of cardiothoracic and vascular anesthesia
Dec 9, 2024
OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.
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