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Biotricity Expands Development of its Cardiac AI Cloud Platform with Data Ecosystem of over 360 billion Heartbeats

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Biotricity Inc. (BTCY) expands its Cardiac AI Cloud platform to support predictive monitoring and earlier interventions. The company has analyzed over 360 billion heartbeats and helped diagnose over 200,000 patients, with products used in 500+ US centers. The expansion aims to enhance existing products, improve operational efficiency, and support physicians with automated analysis.
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  • Biotricity has analyzed over 360 billion heartbeats and helped diagnose over 200,000 patients, demonstrating a strong track record in the medical diagnostic field.
  • The expansion of the Cardiac AI Cloud platform aims to enhance existing products, improve operational efficiency, and support physicians with automated analysis, indicating a commitment to technological advancement and healthcare support.
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Insights

The expansion of Biotricity's Cardiac AI Cloud platform marks a significant stride in the intersection of healthcare and technology. The accumulation of over 360 billion heartbeats and the diagnosis of over 200,000 patients underscore the company's capacity to handle large-scale data analysis. The shift towards predictive AI models could revolutionize cardiac care by facilitating earlier detection and intervention, potentially improving patient outcomes and reducing the burden on healthcare systems.

From a research perspective, the value of extensive longitudinal data cannot be overstated. Continuous monitoring through a 3-channel diagnostic platform, as opposed to more limited 1 or 2 channel systems, offers a more granular view of a patient's cardiac health. This approach can enhance the accuracy of AI models, as the complexity of cardiac conditions often necessitates detailed data to capture intermittent anomalies.

Such advancements could lead to a paradigm shift in how cardiac conditions are managed, moving from reactive to proactive care. The implications for patient quality of life and healthcare cost savings are substantial, potentially leading to a decrease in emergency room visits and hospital readmissions.

The development of predictive technologies in healthcare, such as Biotricity's Cardiac AI Cloud platform, has significant economic implications. By prioritizing early diagnosis and intervention, there is a potential to alleviate the financial strain on healthcare systems caused by chronic cardiac conditions. Reducing readmissions and lowering healthcare costs through improved operational efficiency are key benefits that align with broader objectives in healthcare policy and economics.

Moreover, the scalability of AI-driven platforms means that once the initial investment in technology is absorbed, the marginal cost of serving additional patients is relatively low. This could enable wider access to high-quality cardiac care, especially in underserved areas where specialist care may be limited. In the long term, the shift towards such technology-driven solutions could contribute to bending the cost curve in healthcare, addressing one of the most pressing challenges in the industry today.

Biotricity's initiative to enhance its Cardiac AI Cloud platform is indicative of a broader trend within the medical technology sector. As companies increasingly leverage big data and AI, they gain competitive advantages by offering more sophisticated and efficient diagnostic tools. The predictive capabilities of Biotricity's technology are likely to be a key differentiator in the market, potentially increasing its market share and influencing stock performance.

Investors should note the importance of scalability and operational efficiency in tech-driven healthcare solutions. These factors can lead to wider adoption and increased reliance on Biotricity's technologies by healthcare providers. As the company continues to develop its AI models and expand its product portfolio, it may attract partnerships or acquisition interest, further impacting its market valuation and investor sentiment.

Company's growing data ecosystem supports the development of large data models for its future predictive technologies and Cardiac AI cloud platform

  • Company has analyzed over 360 Billion heartbeats and helped diagnose over 200,000 patients
  • Company is now focused on building predictive AI models to support earlier diagnoses and interventions
  • Existing technologies are used in 500+ centers across the United States

REDWOOD CITY, CA / ACCESSWIRE / January 23, 2024 / Biotricity Inc. (NASDAQ:BTCY) ("Biotricity" or the "Company"), a leading medical diagnostic and consumer healthcare technology company, today announced the expanding development of its future Cardiac AI Cloud platform. The new platform is focused on predictive monitoring to help assist physicians and users to identify issues before they occur, supporting earlier interventions, reducing readmissions, and lowering healthcare costs. Biotricity's product portfolio is already one of the most comprehensive remote cardiac monitoring portfolios globally. This expansion will further enhance its existing products while providing additional advantages such as:

  • Predictive capabilities
  • Faster analytical results
  • Improved scalability
  • Improved operational efficiency
  • Support for other commercial models
  • Automated analysis to support physicians

Biotricity's goal is to develop one the most comprehensive Cardiac AI Cloud platforms. The company has been analyzing and establishing large datasets of heartbeats for the past couple of years to build predictive cardiac AI models for improved diagnoses and faster interventions. The resulting models will help develop more accurate analyses and improved operational efficiency, supporting physicians better and diagnosing more patients with the same resources.

AI and predictive models are difficult to build due to the large datasets needed to support accuracy. Biotricity has been focused on developing large datasets for years. The company's decision to build a 3-channel diagnostic platform as opposed to a 1 or 2 channel platform was a direct result of this focus. Accuracy is difficult to achieve as cardiac issues are notoriously problematic to identify due to their intermittent nature, thus needing long term continuous data for diagnosing.

Long term data collection requires an ambulatory setting with users going about their lives. Ambulatory monitoring is synonymous with noisy data due to mobility, making diagnosis difficult, let alone prediction. To move into predictive monitoring, large data models are needed to overcome the intermittent nature of cardiac issues and the noisy data arising from ambulatory monitoring. AI models built on large ambulatory datasets have the potential to move from delayed diagnoses to instantaneous and predictive diagnoses.

Dr. Waqaas Al-Siddiq, Biotricity Founder and CEO, commented, "Our efforts to build a comprehensive Cardiac AI Cloud is the first step in making cardiac care not only accessible but also affordable and scalable. Today, Cardiologists are overwhelmed with too many patients and too much data, making it difficult for them to service more patients. An accurate cardiac cloud will provide the necessary support and assistance to cardiologists so that they can service more patients and focus on the most relevant pieces of data."

Biotricity has already developed leading edge cardiac technologies that have been deployed commercially with industry leading efficiency. Scalability and accessibility in a market where there is a shortage of healthcare professionals requires smart technologies to help support healthcare professionals to service more patients while improving the quality of care.

To learn more about the groundbreaking solutions in cardiac care that Biotricity has developed, visit www.biotricity.com.

About Biotricity Inc.

Biotricity is reforming the healthcare market by bridging the gap in remote monitoring and chronic care management. Doctors and patients trust Biotricity's unparalleled standard for preventive & personal care, including diagnostic and post-diagnostic solutions for chronic conditions. The company develops comprehensive remote health monitoring solutions for the medical and consumer markets. To learn more, visit www.biotricity.com.

Important Cautions Regarding Forward-Looking Statements

Any statements contained in this press release that do not describe historical facts may constitute forward-looking statements. Forward-looking statements, which involve assumptions and describe our future plans, strategies, and expectations, are generally identifiable by use of the words "may," "should," "would," "will," "could," "scheduled," "expect," "anticipate," "estimate," "believe," "intend," "seek," "project," or "goal" or the negative of these words or other variations on these words or comparable terminology. Forward-looking statements may include, without limitation, statements regarding (i) the plans, objectives and goals of management for future operations, including plans, objectives or goals relating to the design, development and commercialization of Bioflux or any of the Company's other proposed products or services, (ii) a projection of income (including income/loss), earnings (including earnings/loss) per share, capital expenditures, dividends, capital structure or other financial items, (iii) the Company's future financial performance, (iv) the regulatory regime in which the Company operates or intends to operate and (v) the assumptions underlying or relating to any statement described in points (i), (ii), (iii) or (iv) above. Such forward-looking statements are not meant to predict or guarantee actual results, performance, events or circumstances and may not be realized because they are based upon the Company's current projections, plans, objectives, beliefs, expectations, estimates and assumptions and are subject to a number of risks and uncertainties and other influences, many of which the Company has no control over. Actual results and the timing of certain events and circumstances may differ materially from those described by the forward-looking statements as a result of these risks and uncertainties. Factors that may influence or contribute to the inaccuracy of the forward-looking statements or cause actual results to differ materially from expected or desired results may include, without limitation, the Company's inability to obtain additional financing, the significant length of time and resources associated with the development of its products and related insufficient cash flows and resulting illiquidity, the Company's inability to expand the Company's business, significant government regulation of medical devices and the healthcare industry, lack of product diversification, existing or increased competition, results of arbitration and litigation, stock volatility and illiquidity, and the Company's failure to implement the Company's business plans or strategies. These and other factors are identified and described in more detail in the Company's filings with the SEC. There cannot be any assurance that the Company will ever become profitable.

CONTACTS

Investor Relations
Biotricity Investor Relations
Investors@biotricity.com

SOURCE: Biotricity, Inc.



View the original press release on accesswire.com

FAQ

What is Biotricity's ticker symbol?

Biotricity's ticker symbol is BTCY.

How many heartbeats has Biotricity analyzed?

Biotricity has analyzed over 360 billion heartbeats.

How many patients has Biotricity helped diagnose?

Biotricity has helped diagnose over 200,000 patients.

Where are Biotricity's products used?

Biotricity's products are used in 500+ centers across the United States.

What is the focus of Biotricity's expanding Cardiac AI Cloud platform?

The focus is on predictive monitoring to assist physicians and users to identify issues before they occur, supporting earlier interventions, reducing readmissions, and lowering healthcare costs.

What are the advantages of the expanding Cardiac AI Cloud platform?

Advantages include predictive capabilities, faster analytical results, improved scalability, improved operational efficiency, support for other commercial models, and automated analysis to support physicians.

Why did Biotricity decide to build a 3-channel diagnostic platform?

The decision was a direct result of the focus on developing large datasets for accurate predictive cardiac AI models.

Why is accuracy difficult to achieve in building predictive cardiac AI models?

Accuracy is difficult to achieve due to the intermittent nature of cardiac issues, necessitating long-term continuous data for diagnosing.

What setting is required for long-term data collection?

Long-term data collection requires an ambulatory setting with users going about their daily activities.

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