About Universe Scientific Publishing

Universe Scientific Publishing (USP) was established with the aim of providing a publishing platform for all scholars and researchers around the world. With this aim in mind, USP began building up its base of journals in various fields since its establishment.

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Our books

  • 探矿工程与地质灾害..

    ISBN:978-981-5092-63-9

  • 南曲语音..

    ISBN:978-981-17215-0-2

  • 数字经济法治保护研..

    ISBN:978-981-94-2273-9

  • Inheritan..

    ISBN:978-981-94-2464-1

  • 人工智能在资产评估..

    ISBN:978-981-94-2551-8

  • 基于 Chat G..

    ISBN:978-981-94-2552-5

  • 现代城乡规划设计研..

    ISBN:978-981-94-2720-8

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A new approach may improve the treatment of patients with cardiovascular problems.

Eko, a digital health company building AI-powered screening and telehealth solutions to fight cardiovascular disease, announced that the U.S. Food and Drug Administration (FDA) has issued the company an Emergency Use Authorization (EUA) for its novel ECG-based algorithm that can provide an easily accessible, rapid screening test for low ejection fraction (low EF), a weak heart pump.

Awarded an FDA Breakthrough Device designation in December 2019, the algorithm’s regulatory review has been further accelerated due to its potential to assist providers in identifying patients with abnormal heart function during the COVID-19 pandemic.

[Source:https://finance.yahoo.com/news/fda-issues-emergency-authorization-eko-110000542.html]


Artificial intelligence algorithms have achieved a very good results in the fields of speech and images. Therefore, their application to the field of electrocardiography is a direction worth exploring, as an article published on the Journal Probe - Computer Science & Information Technology stated.

In this paper, the authors present a new approach of an adaptive filter high performance based on abstract data types for processing ECG signals, tested in conventional central processing unit (CPU) and Graphics Processing Unit (GPU), evaluated for its efficiency from the samples obtained from the MIT-BIH, arrhythmia database. The algorithm used is based on a compact genetic algorithm that was based on abstract data types, implemented in MATLAB in architecture CUDA.

The results have shown that the compact genetic algorithm can be implemented in high-performance systems, aiming to improve the health care systems of treatment is provided to patients with cardiovascular problems.

Read the full paper at : http://probe.usp-pl.com/index.php/CSIT/article/view/1254