AIMC Topic: Middle Aged
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Machine learning for predicting acute myocardial infarction in patients with sepsis.
Scientific reports
Dec 24, 2024
Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in intensive care units. While sepsis frequently affects the cardiovascular system, distinguishing between sepsis-induced cardiomyopathy and AMI remains chall...
Pulmonologists-level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach.
Scientific reports
Dec 24, 2024
Lung cancer (LC) remains the primary cause of cancer-related mortality, largely due to late-stage diagnoses. Effective strategies for early detection are therefore of paramount importance. In recent years, machine learning (ML) has demonstrated consi...
Longitudinal interpretability of deep learning based breast cancer risk prediction.
Physics in medicine and biology
Dec 24, 2024
Deep-learning-based models have achieved state-of-the-art breast cancer risk (BCR) prediction performance. However, these models are highly complex, and the underlying mechanisms of BCR prediction are not fully understood. Key questions include wheth...
Nonlinear relationship between serum Klotho and chronic kidney disease in US adults with metabolic syndrome.
Frontiers in endocrinology
Dec 24, 2024
BACKGROUND: Current evidence regarding the effects of serum Klotho among patients with metabolic syndrome (MetS) is scarce. This study explored the relationship between serum Klotho levels and the odds of chronic kidney disease (CKD) in middle-aged a...
Robust and interpretable deep learning system for prognostic stratification of extranodal natural killer/T-cell lymphoma.
European journal of nuclear medicine and molecular imaging
Dec 23, 2024
PURPOSE: Extranodal natural killer/T-cell lymphoma (ENKTCL) is an hematologic malignancy with prognostic heterogeneity. We aimed to develop and validate DeepENKTCL, an interpretable deep learning prediction system for prognosis risk stratification in...
Artificial Intelligence Recognition System of Pelvic Autonomic Nerve During Total Mesorectal Excision.
Diseases of the colon and rectum
Dec 23, 2024
BACKGROUND: The preservation of the pelvic autonomic nervous system in total mesorectal excision remains challenging to date. The application of laparoscopy has enabled visualization of fine anatomical structures; however, the rate of urogenital dysf...
Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.
Journal of cardiovascular electrophysiology
Dec 23, 2024
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates partly due to the considerable heterogeneity within the patient population. Identifying distinct patient phenotypes based on post-ablation prognosis co...
Machine learning in personalized laryngeal cancer management: insights into clinical characteristics, therapeutic options, and survival predictions.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Dec 23, 2024
PURPOSE: Over the last 40 years, there has been an unusual trend where, even though there are more varied treatments, survival rates have not improved much. Our study used survival analysis and machine learning (ML) to investigate this odd situation ...
Volumetric Artificial Intelligence Analysis of Prerupture and Postrupture Cerebral Aneurysms: Assessment of Morphologic Change.
World neurosurgery
Dec 23, 2024
BACKGROUND: Cerebral aneurysm rupture is a major cause of potential years of life lost. Research on rupture risk has often compared unruptured and ruptured aneurysms, with the implicit assumption that the rupture event does not significantly change a...
Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.
Sensors (Basel, Switzerland)
Dec 23, 2024
Freezing of gait (FOG) is a walking disturbance that can lead to postural instability, falling, and decreased mobility in people with Parkinson's disease. This research used machine learning to predict and detect FOG episodes from plantar-pressure da...
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