AIMC Topic: Retrospective Studies
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Machine learning-based pipeline for automated intracerebral hemorrhage and drain detection, quantification, and classification in non-enhanced CT images (NeuroDrAIn).
PloS one
Dec 26, 2024
BACKGROUND AND PURPOSE: External drainage represents a well-established treatment option for acute intracerebral hemorrhage. The current standard of practice includes post-operative computer tomography imaging, which is subjectively evaluated. The im...
Identifying potential medical aid beneficiaries using machine learning: A Korean Nationwide cohort study.
International journal of medical informatics
Dec 25, 2024
OBJECTIVE: To identify potential medical aid beneficiaries using demographic and medical history of individuals and analyzing important features qualitatively.
Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters.
Neurologia medico-chirurgica
Dec 25, 2024
This study aimed to investigate the patterns of anticoagulation therapy and coagulation parameters and to develop a prediction model to predict the type of anticoagulation therapy in geriatric patients with traumatic brain injury. A retrospective ana...
12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.
Journal of electrocardiology
Dec 25, 2024
BACKGROUND AND PURPOSE: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electrical and structural changes, notably low voltage areas (LVAs) which are associated with poor ablation outcomes and increased thromboembolic risk. This ...
Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma.
BMC cancer
Dec 25, 2024
BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) exhibits a propensity for early recurrence following liver resection, resulting in a bleak prognosis. At present, majority of the predictive models for the early postoperative recurrence of HCC rely...
Machine Learning Model for Risk Prediction of Prolonged Intensive Care Unit in Patients Receiving Intra-aortic Balloon Pump Therapy during Coronary Artery Bypass Graft Surgery.
Journal of cardiovascular translational research
Dec 24, 2024
This study aimed to construct machine learning models and predict prolonged intensive care units (ICU) stay in patients receiving perioperative intra-aortic balloon pump (IABP) therapy during cardiac surgery. 236 patients were divided into the normal...
Intensive Care Units
Female
Reproducibility of Results
Risk Factors
Aged
Humans
Machine Learning
Decision Support Techniques
Retrospective Studies
Time Factors
Treatment Outcome
Predictive Value of Tests
Coronary Artery Bypass
Male
Intra-Aortic Balloon Pumping
Middle Aged
Risk Assessment
Length of Stay
Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.
European journal of radiology
Dec 24, 2024
OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning ...
Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models.
Indian journal of ophthalmology
Dec 24, 2024
PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.
Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.
Respiratory research
Dec 24, 2024
BACKGROUND: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI...
Analysis of the basement membrane-related genes ITGA7 and its regulatory role in periodontitis via machine learning: a retrospective study.
BMC oral health
Dec 24, 2024
BACKGROUND: Periodontitis is among the most prevalent inflammatory conditions and greatly impacts oral health. This study aimed to elucidate the role of basement membrane-related genes in the pathogenesis and diagnosis of periodontitis.
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