AIMC Topic: Cohort Studies
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Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome.
Clinica chimica acta; international journal of clinical chemistry
Aug 6, 2024
BACKGROUND: A poor prognosis is associated with atherosclerotic plaque rupture (PR) despite after conventional therapy for patients with acute coronary syndrome (ACS). Timely identification of PR improves the risk stratification and prognosis of ACS ...
Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts.
BMC public health
Aug 6, 2024
BACKGROUND: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle i...
Machine learning in diagnostic support in medical emergency departments.
Scientific reports
Aug 2, 2024
Diagnosing patients in the medical emergency department is complex and this is expected to increase in many countries due to an ageing population. In this study we investigate the feasibility of training machine learning algorithms to assist physicia...
Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.
NPJ systems biology and applications
Aug 2, 2024
Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks inform...
Establishment and validation of an artificial intelligence web application for predicting postoperative in-hospital mortality in patients with hip fracture: a national cohort study of 52 707 cases.
International journal of surgery (London, England)
Aug 1, 2024
BACKGROUND: In-hospital mortality following hip fractures is a significant concern, and accurate prediction of this outcome is crucial for appropriate clinical management. Nonetheless, there is a lack of effective prediction tools in clinical practic...
Machine Learning Predicts Patients With New-onset Diabetes at Risk of Pancreatic Cancer.
Journal of clinical gastroenterology
Aug 1, 2024
BACKGROUND: New-onset diabetes represent a high-risk cohort to screen for pancreatic cancer.
Age Reduction After Face-Lift Surgery in Chinese Population: An Outcome Study Using Artificial Intelligence and Objective Observer-Based Assessment.
Aesthetic plastic surgery
Jul 31, 2024
BACKGROUND: The literature is replete with favorable face-lift results, yet the objective facial rejuvenation outcome measures in Chinese women have remained poorly understood.
Machine learning uncovers manganese as a key nutrient associated with reduced risk of steatotic liver disease.
Liver international : official journal of the International Association for the Study of the Liver
Jul 31, 2024
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 20%-30% of the general population and is linked to high-caloric western style diet. However, there are little data that specific nutrients might help t...
A Novel Machine-Learning Algorithm to Predict the Early Termination of Nutrition Support Team Follow-Up in Hospitalized Adults: A Retrospective Cohort Study.
Nutrients
Jul 31, 2024
BACKGROUND: For hospitalized adults, it is important to initiate the early reintroduction of oral food in accordance with nutrition support team guidelines. The aim of this study was to develop and validate a machine learning-based algorithm that pre...
Machine learning-derived prognostic signature for progression-free survival in non-metastatic nasopharyngeal carcinoma.
Head & neck
Jul 30, 2024
BACKGROUND: Early detection of high-risk nasopharyngeal carcinoma (NPC) recurrence is essential. We created a machine learning-derived prognostic signature (MLDPS) by combining three machine learning (ML) models to predict progression-free survival (...
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