Embracing Change: How AI Will Help Us Predict Disease

Estimated reading time: 4-6 minutes

In this new era of healthcare, we have to get better at helping people maintain equilibrium and preventing disease. Artificial intelligence could hold the key.

Technology is constantly evolving and changing the way we work. I remember a distinct shift in my own career when three-dimensional echocardiography was developed and started to be adopted more widely. In my early career as a cardiologist, I became an expert in 3D echocardiography and began teaching others how to do it. This was a sought-after skill, one that I was proud of. All of a sudden, technology evolved, allowing any clinician with less experience to effectively measure left ventricular ejection fraction by 3D echocardiography with reliable and reproducible results. It no longer had to be me. At that time, I thought to myself, “Okay, I need to do something else!”

Faced with an aging population with growing needs, and overburdened healthcare systems treating people for progressed and complex illness, we must reduce healthcare costs and keep people living a good quality of life for longer. To do this, we have to focus on predicting and preventing disease.

Biomarkers of the future

To forge this path, larger efforts will have to be made to deepen our understanding of biomarkers and unlock their full potential. These subtle hints can help predict disease, infection or environmental exposure by indicating that certain processes in the body are functioning abnormally. For example, elevated cholesterol levels are a marker for higher risk of heart disease. However, while routine screening of cholesterol levels is common in clinical practice, the assessment of our genetic footprint, or DNA profile, in the clinical setting is still limited to very specific conditions. Interestingly, our genes may indicate a higher risk for certain diseases, especially when environmental or behavioral factors are added to the equation. Improving our understanding of the genetic profile in different populations will expand our capacity to educate patients and prevent disease in a personalized manner.

Moreover, digital technology like wearables, smart monitoring and connected devices generate an enormous amount of round-the-clock data that can be stored and analyzed for the discovery of biomarkers. The traditional definition of biomarkers referring to biological molecules in tissue, blood, or other body fluids, has been expanding to include imaging and other kinds of data that healthcare professionals can gather predictive insights from. That’s where artificial intelligence comes in, helping to organize and analyze all of this data. Once the clinical understanding of this population data from wearables is incorporated into clinical practice, clinicians will have a wider range of options to improve their understanding of the individual patient, helping them predict and consequently prevent specific diseases.

AI as a tool for clinicians, not a replacement

As with all changes, there are some concerns with the implementation of AI:

Overflow of data is becoming overwhelming for clinicians. All of the patient data captured in our digital world can exceed understanding and limit time to provide quality patient care. Artificial intelligence (AI) will bridge this gap and help clinicians interpret biomarkers and derive actionable results.
Expanding use of AI in healthcare has caused some providers to feel threatened by this emerging technology, uncertain of their role once AI has proven to be effective for certain applications. It’s true, there are certain functions that artificial intelligence could perform independently, but these are only pieces of the larger puzzle.
The purely quantitative methodology driving AI operations and recommendations causes some concern. For example, with ultrasound imaging, AI can analyze images and accompanying information and then quantify and classify them, but without involvement from the clinician, important nuances only achievable by patient communication could easily be lost. The final calls have to be made by a person who sees beyond the machine, who looks at a patient as an individual and is able to make an integrative interpretation putting it all in context.

I believe we as healthcare providers must adapt and embrace any new technology that is able to demonstrate its ability to improve patient care and help us move toward a more preventative care model. The computational power and time-saving assistance of AI may do just that, especially in certain circumstances. Leveraging these advances also means clinicians can take more time deepening the relationship with their patients face-to-face.

My vision for the future is for all healthcare providers to invest to have the tools they need to diagnose people earlier, in order to mitigate disease at the earliest stages. And I believe we are not far from making this a reality.

About Innovation Matters

Innovation Matters delivers news, opinions and features about healthcare, and is focused on the professionals who work within the industry, as well as Philips as a cutting-edge health technology organization. From interviews with industry giants to how-to guides and features powered by Philips data, our goal is to deliver interesting, educational and entertaining content to empower and inspire all those who work in healthcare or related industries.

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Alexandra Gonçalves, MD, MMSc, PhD

Chief Medical Officer, Precision Diagnosis, Philips
Alexandra Gonçalves is Chief Medical Officer, Precision Diagnosis for Philips. Dr. Goncalves is a cardiologist with a business acumen and an extensive record of multi-disciplinary collaborations spanning the globe, as educator, author, editor, clinical researcher and though leader.

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