AI-Powered Remote Heart Monitoring Transforms Heart Health Model from Reactive to Proactive with Dr. Waqaas Al-Siddiq Biotricity TRANSCRIPT
Release Date: 12/09/2025
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info_outlineEmpowered Patient Podcast
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Dr. Kumar Dharmarajan, cardiologist and geriatrician and Co-Founder and Chief Medical Officer at World Class Health, is bringing concierge healthcare to employees of self-insured companies. The platform includes a global network of top-tier doctors and nurse navigators. Directly negotiating with providers reduces costs and reduces administrative and financial friction for patients seeking planned procedures. The model also reduces friction for physicians by providing them with complete patient records and ensuring prompt payment. Kumar explains, "We are a global,...
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Brent Dial, Founder and CEO of Beek Health, has built a platform that addresses patient information fragmentation by aggregating data from patient portals and providing direct access to lab testing. Health literacy is key to preventing chronic diseases, and AI is being used to scale the delivery of personalized health information. Identifying relevant biomarkers and early warning signs supports proactive health management that can alter long-term health outcomes. Brent explains, "Beek Health is re-imagining healthcare by finally putting the individual at the center of their health journey....
info_outlineDr. Waqaas Al-Siddiq, CEO and Founder of Biotricity, has designed a direct-to-consumer service to shift healthcare from a reactive to a preventive model by simplifying and accelerating access to remote cardiac screening. Applying AI to sift through patient data allows the cardiologist to focus on clinically relevant information and to identify sporadic, intermittent heart issues that are often difficult to detect using traditional heart screening techniques. Waqaas predicts an expansion of specialized solutions using AI and large datasets to support clinicians and patients in the drive to identify early signs of disease.
Waqaas explains, "The thing that we've been focused on is, as you know, heart issues. We've talked extensively about heart issues, which are the number one killer. And so what we've done now is we've collected this massive dataset, but we're trying to look at the nuances of those needles in a haystack. So it's not about the individuals who have arrhythmias to catch. It's about the ones who are very, very sporadic and intermittent, something that happens once every four months. Is there a way to predict that? Can we grab additional data from the patient about their environment, about their history, to get a more holistic view of the patient? "
"Often, with a massive amount of data in a set, you can get into prediction, but you need a more holistic view. Our focus has now been on now that we've captured 90% of the scenarios, the last 10% are incredibly complicated, and how do we leverage that? How do we use our data to basically get into those specialized nuances?"
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