Background: Age and sex can be estimated using artificial intelligence on the basis of various sources. The aims of this study were to test whether convolutional neural networks could be trained to estimate age and predict sex using standard transthoracic echocardiography and to evaluate the prognostic implications.
Methods: The algorithm was trained on 76,342 patients, validated in 22,825 patients, and tested in 20,960 patients.
Background: We aimed to assess in a prospective multicenter study the quality of echocardiographic exams performed by inexperienced users guided by a new artificial intelligence software and evaluate their suitability for diagnostic interpretation of basic cardiac pathology and quantitative analysis of cardiac chamber and function.
Methods: The software (UltraSight, Ltd) was embedded into a handheld imaging device (Lumify; Philips). Six nurses and 3 medical residents, who underwent minimal training, scanned 240 patients (61±16 years; 63% with cardiac pathology) in 10 standard views.
Background: Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality. Acute exacerbations of COPD (AECOPD) drastically affect the clinical course of the disease. We aimed to evaluate the treatment of AECOPD in the internal medicine departments in Israel, nationwide.
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