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Article
Open AccessDevelopment and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the population level
Artificial intelligence-enabled electrocardiogram (ECG) algorithms are gaining prominence for the early detection of cardiovascular (CV) conditions, including those not traditionally associated with convention...
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Article
Open AccessTowards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms
The feasibility and value of linking electrocardiogram (ECG) data to longitudinal population-level administrative health data to facilitate the development of a learning healthcare system has not been fully ex...
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Article
Open AccessExtending schizophrenia diagnostic model to predict schizotypy in first-degree relatives
Recently, we developed a machine-learning algorithm “EMPaSchiz” that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia...
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Article
Open AccessTowards artificial intelligence in mental health by improving schizophrenia prediction with multiple brain parcellation ensemble-learning
In the literature, there are substantial machine learning attempts to classify schizophrenia based on alterations in resting-state (RS) brain patterns using functional magnetic resonance imaging (fMRI). Most e...
