MedCity Influencers, Artificial Intelligence

How artificial intelligence will shape the physician toolkit in 2019

As we consider AI’s expansion across the entire healthcare industry, here are some specific areas where I believe artificial intelligence will make the most impact in 2019, as it continues to shape the modern physician’s toolkit.

The healthcare AI market is projected to reach $34 billion worldwide by 2025, according to Tractica, and this momentum is creating both fear and excitement about its role in the years to come. While one school of thought worries that artificial intelligence may render physicians’ jobs as obsolete, others believe that it will only be an asset to the industry. I subscribe to the second school of thought: Artificial intelligence will never replace doctors, but rather will serve as a tool to help them achieve greater results.

In 2019, the partnership between AI and humans in the healthcare industry will become more mainstream, as more physicians investigate and adopt the technologies utilizing artificial intelligence in their hospitals to witness the impact of AI on their own practice.

As an industry today, we’ve just begun to realize the tremendous potential AI has to transform the way physicians deliver high-quality, cost-effective, diagnostic and treatment services. In order to achieve this level of economic impact, there must be more education and resources detailing the real-world, positive influence AI yields at the patient, provider and payer levels. Additionally, the necessary infrastructure must be in place to maximize the day-to-day impact on care decisions.

As we consider AI’s expansion across the entire healthcare industry, here are some specific areas where I believe AI will make the most impact in 2019, as it continues to shape the modern physician’s toolkit.

Diagnosis and Treatment Decisions: AI as a Partner in Care
In 2019, the processing power of AI applications will span far beyond helping physicians with simple diagnoses. It will be used to help physicians identify the severity of what is wrong with the patient and provide insight into why they are experiencing symptoms. This context will help doctors decide on the most effective treatment for that particular patient.

Two example diseases in which I believe we’ll see a larger AI influence on diagnosis decisions are coronary heart disease and cancer. For coronary heart disease, AI will build on the benefits of coronary CT scans. After a patient receives a coronary CT scan, AI can be applied to create accurate and precise quantitative 3D models of the patient’s arteries, including areas of disease and blockage that limit blood supply to the heart muscle.

These AI-enabled models can then be used in conjunction with powerful computer algorithms applied to solve the complex equations of blood flow and assess the impact of blockages, aiding physicians in determining, vessel by vessel, if sufficient blood is reaching the heart. The level of detail provided will help ensure that physicians understand the extent of disease and develop the best pathway for care.

Outside of cardiology, AI-trained detection algorithms will help physicians mark-up tumor boundaries on imaging scans for cancer patients. After a scan has been completed, AI tools will map out the organ on each image and create a 3D model, which can then be assessed by a physician to accurately detect tumors. This practice will help physicians become more efficient and speed up the reliability of cancer diagnoses and enable more targeted treatment decisions.

Remote Care: Improving the Patient Feedback Loop with AI
AI’s impact won’t only be felt inside the hospital walls, but will also have a significant influence on managing conditions. Once patients leave their direct care, it can be difficult for physicians to ensure that the patient is complying with prescribed treatment plans or to monitor chronic health conditions. That’s where AI comes in. We’re already seeing remote monitoring tools and apps built into gadgets or smartwatches, providing the ability for consumers to securely share health information with their physicians.

The announcement of the new Apple Watch ability to record electrocardiograms (ECGs) and use AI to detect common heart arrhythmias means that other fitness trackers must also begin introducing clinical applications for their devices or run the risk of being left behind. As we see this market expand, we’ll also see new applications for collecting in-the-moment data from consumers and turning it into insights to be used by their physicians. This data will help physicians keep up-to-date on their patients’ health and fill in the gaps between appointments.

2019 brings tremendous potential for artificial intelligence to enhance the physician workflow, increasing efficiency and confidence in their care decisions for patients. However, in order to reach physicians in the first place, AI technology companies must put the time into first understanding and appreciating the medical problems, then developing these tools and pushing them through the appropriate regulatory pathway.

Policy makers and healthcare professionals naturally take a cautious approach when evaluating new technologies for patient care, as people’s lives can be at stake. It’s critical for the proper clinical research to be undertaken and continued through the lifecycle of the product. In turn, physicians, hospitals and payers will begin to take a more open-minded approach to AI’s potential as the proper research and benefits are proven. 2019 will be a breakthrough year for AI and I am excited to see the partnership between AI and the healthcare industry continue to grow and strengthen.

 

 

 


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Charles Taylor

Charles A. Taylor, Ph.D. is the Founder, Chief Technology Officer, and Member of the Board of Directors of HeartFlow. Previously, he was an Associate Professor in the Departments of Bioengineering and Surgery at Stanford University with courtesy faculty appointments in the Departments of Mechanical Engineering and Radiology. He is also currently a Consulting Professor of Bioengineering at Stanford University and a Part-time Professor of Biomedical Engineering at the Technical University of Eindhoven. He is internationally recognized for his pioneering work in combining computer simulation methods with medical imaging data for patient-specific modeling of blood flow to aid in the diagnosis and treatment of cardiovascular disease. Dr. Taylor has published over 350 peer-reviewed journal and conference papers and has over 220 issued or pending patents worldwide.

He received his B.S. degree in Mechanical Engineering, M.S. degree in Mechanical Engineering and M.S. degree in Mathematics from Rensselaer Polytechnic Institute and a Ph.D. in Mechanical Engineering from Stanford University.

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