Ecotoxicology and environmental safety
Dec 24, 2024
Machine learning exhibits excellent performance in terms of predictive power. We aimed to construct an interpretable machine learning model utilizing National Health and Nutrition Examination Survey data to investigate the relationship between heavy ...
The gut microbiota is a crucial link between diet and cardiovascular disease (CVD). Using fecal metaproteomics, a method that concurrently captures human gut and microbiome proteins, we determined the crosstalk between gut microbiome, diet, gut healt...
BACKGROUND: Ischemic heart disease is a leading cause of death globally with a disproportionate burden in low- and middle-income countries (LMICs). Natural language processing (NLP) allows for data enrichment in large datasets to facilitate key clini...
BACKGROUND: Electronic medical records (EMR)-trained machine learning models have the potential in CVD risk prediction by integrating a range of medical data from patients, facilitate timely diagnosis and classification of CVDs. We tested the hypothe...
Oral surgery, oral medicine, oral pathology and oral radiology
Dec 18, 2024
OBJECTIVES: This study evaluated an automated deep learning method for detecting calcifications in the extracranial and intracranial carotid arteries and vertebral arteries in cone beam computed tomography (CBCT) scans. Additionally, a model utilizin...
OBJECTIVE: To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction.
International journal of medical informatics
Dec 1, 2024
BACKGROUND: The 12-lead electrocardiogram (ECG) is an established modality for cardiovascular assessment. While deep learning algorithms have shown promising results for analyzing ECG data, the limited availability of labeled datasets hinders broader...
BACKGROUND: Artificial intelligence (AI)-based models are increasingly being integrated into cardiovascular medicine. Despite promising potential, racial and ethnic biases remain a key concern regarding the development and implementation of AI models...
International journal of molecular sciences
Nov 30, 2024
Metabolomic data often present challenges due to high dimensionality, collinearity, and variability in metabolite concentrations. Machine learning (ML) application in metabolomic analyses is enabling the extraction of meaningful information from comp...
BACKGROUND: Over the last few decades: heart disease (HD) has emerged as one of the deadliest diseases in the world. Approximately more than 31 % of the population dies from HD each year. The Diagnosis of HD in an earlier stage is a cognitively chall...
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