THE USE INTEGRATION OF MACHINE LEARNING FOR CARDIOVASCULAR DISEASE DIAGNOSIS - Просвиркина, Елена Владимировна; Сахарчук, Алексей Юрьевич; Попов, Дмитрий Михайлович; Руднев, Сергей Дмитриевич (Medicine in Kuzbass, 2025)
The aim of the research – the possibility of using deep learning neural networks for diagnosing cardiovascular diseases with remote access to the global Internet investigated.Materials and methods. The method of comparative analysis of devices for conducting electronic auscultation and the corresponding software was used. Transfer learning provided by the Teachable Machine web service to obtain a predictive model used. The JavaScript programming language, the TensorFlow.js machine learning library, and the Speech Command Recognizer to develop the web application were used.Results. The proposed model on test datasets in the remote diagnostics mode on the global Internet was developed and tested. In real time with connecting the electronic stethoscope to the audio input of a personal computer was performed. The proposed model on the datatset of audio showed the possibility of diagnosing cardiac abnormalities with an accuracy of more than 90% were tested.
Keywords: cardiovascular diseases; electronic stethoscope; machine learning; model