AiSteth, this next-gen smart stethoscope diagnoses heart-related issues in minutes

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Chaitanyesh
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AiSteth, this next-gen smart stethoscope diagnoses heart-related issues in minutes
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  • AI stethoscope developed to swiftly identify heart ailments in minutes
  • This next-generation smart stethoscope enables users to visualize sound
  • It also facilitates anomaly detection through AI and ML technologies

As the prevalence of heart-related issues continues to increase, a groundbreaking AI stethoscope has been developed to swiftly identify such concerns within minutes. Manju DV, a co-founder of the company spearheading this innovative device, elucidates its functionality.

Named AiSteth, this next-generation smart stethoscope not only enables users to visualize sound, but also facilitates anomaly detection through integration with artificial intelligence and machine learning technologies.

Ai Health Highway, an AI-centric company, is committed to making the screening of chronic diseases cost-effective at primary care clinics—the initial point of contact for patients.

Given that 43 million people succumb to Noncommunicable Diseases (NCDs) annually, accounting for 71% of global deaths, Ai Health Highway aims to reduce premature deaths resulting from NCDs by 25% by the year 2025. The company is dedicated to advancing early detection and prediction of heart and lung disorders.

The AiSteth, equipped with state-of-the-art signal processing and ML capabilities, holds the potential to screen, detect, and predict heart and lung disorders.

Speaking to NewsFirst Prime, Manju DV emphasized the company's focus on the health industry, particularly in addressing heart-related issues. By 2025, their objective is to achieve a 25% reduction in such issues. Having commenced development in 2019, the device has demonstrated an impressive accuracy rate of 98.3%.

Furthermore, Ai Health Highway has successfully implemented AiSteth in various primary health centers. Over the course of their efforts, they have screened 25,000 individuals, identifying abnormalities in 3,000 cases, all of which were subsequently referred for further evaluation.

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