AIMC Topic: Incidence

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Impact of artificial intelligence on colorectal polyp detection.

Best practice & research. Clinical gastroenterology
Since colonoscopy and polypectomy were introduced, Colorectal Cancer (CRC) incidence and mortality decreased significantly. Although we have entered the era of quality measurement and improvement, literature shows that a considerable amount of colore...

Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models.

BMC medical research methodology
BACKGROUND: Accurate forecasting model for under-five mortality rate (U5MR) is essential for policy actions and planning. While studies have used traditional time series modeling techniques (e.g., autoregressive integrated moving average (ARIMA) and ...

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning.

Computational and mathematical methods in medicine
Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of a...

Artificial Intelligence-Electrocardiography to Predict Incident Atrial Fibrillation: A Population-Based Study.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI-enabled electrocardiogr...

Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data.

BMC medical informatics and decision making
BACKGROUND: With cardiovascular disease increasing, substantial research has focused on the development of prediction tools. We compare deep learning and machine learning models to a baseline logistic regression using only 'known' risk factors in pre...

Long-term PM exposure and the clinical application of machine learning for predicting incident atrial fibrillation.

Scientific reports
Clinical impact of fine particulate matter (PM) air pollution on incident atrial fibrillation (AF) had not been well studied. We used integrated machine learning (ML) to build several incident AF prediction models that include average hourly measurem...

Identification of risk features for complication in Gaucher's disease patients: a machine learning analysis of the Spanish registry of Gaucher disease.

Orphanet journal of rare diseases
BACKGROUND: Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the disease have changed. However, there remain unmet needs such as the identification of patients at ris...