The advent of Artificial Intelligence (AI) has revolutionised health care over the past decade by transforming the way physicians diagnose, treat, and manage diseases, and by making medical services more efficient, accurate, and personalised. This, in turn, helps clinicians to ensure that all patients receive precise, evidence-based treatment, irrespective of age, gender, or existing comorbidities.
Studies have suggested that young people face age-related optimism bias — essentially, doctors may underestimate their risk and delay treatment, leading to worse outcomes
On World Heart Day, let us consider the grave challenge before us, where AI can be of use. According to the World Health Organization (WHO), cardiovascular diseases (CVDs) are the primary cause of morbidity and mortality in the world, representing an estimated 17.9 million deaths — a whopping 31% of all deaths across the globe.
India is one of the countries most burdened by CVDs, thus earning the moniker “the heart attack capital of the world”. Even worse, a notable number of cardiac-related deaths occur in individuals under the age of 50 years — a decade earlier than those living in western countries. This shockingly high number of patients suffering from CVDs has necessitated finding ways to accurately identify and treat “at-risk” individuals before they fall prey to this deadly disease.
Over the past decade or so, science has advanced in leaps and bounds, introducing new and sophisticated tools for more precisely diagnosing and predicting the future development of diseases. The field of therapeutics has also advanced considerably. While these developments empower physicians to treat the patients better, the availability of the vast amount of health care data also overwhelms human capacity. It has become nearly impossible for doctors and other health care professionals to assimilate the available information, draw the most precise conclusions and make the most accurate treatment decisions.
This is where AI steps in — not only can its algorithms help sift through vast amounts of clinical data in a fraction of the time that it would take a human, it can also help identify patterns and predict health risks, leading to earlier and more precise interventions and improved patient outcomes.
In cardiac illnesses, AI can help analyse and assimilate medical information from various diagnostic tools such as electrocardiograms (ECGs), echocardiograms, stress tests, CT scans, and even from wearable devices, integrate it with the available clinical and laboratory data, and identify subtle patterns and changes that would be invisible to the human eye. This not only allows very early identification of individuals who are at the highest risk and need the most attention, it also enables clinicians to make the most accurate treatment decisions at every stage of the disease process.
But despite these advances, challenges in ensuring consistent and unbiased treatment persist. For example, younger cardiovascular patients often experience disparity with respect to receiving optimal medical treatment. Studies have suggested that young people face age-related optimism bias — essentially, doctors may underestimate their risk and delay treatment, leading to worse outcomes. The symptoms of younger cardiovascular patients are often dismissed as minor, attributed to work-related stress, or are considered unlikely to be linked to serious illness. This can lead to delays in diagnosis and treatment.
Intervening early in cardiovascular cases is important because it helps prevent minor issues from progressing into life-threatening conditions such as heart attacks, strokes, or heart failure. Timely diagnosis and treatment can reduce damage to the heart and blood vessels, improve recovery outcomes, and lower the chances of long-term complications. AI models may help here: Its algorithms can help physicians improve patient-specific decision-making.
Separately, several observers note that AI can help improve access to health care in rural areas, address a shortage of trained medical professionals, as well as assist at busy hospitals.
However, we must be careful: After all, AI is merely a support tool that we doctors can use to help diagnose and treat a disease. AI cannot help in cases where the patients themselves may not recognise the symptoms of a disease — or may delay seeking medical attention — which can allow the underlying conditions to progress unchecked.
AI merely provides the doctor with data, it is up to the doctor to provide a medical context to the information he or she receives. AI analysis also heavily depends on the quality and diversity of the data — poor data can result in misinterpretation that experienced physicians would otherwise recognise.
To conclude, I would like to quote the science fiction writer, Isaac Asimov: “The machine is only a tool after all, which can help humanity progress faster by taking some of the burdens of calculations and interpretations off its back. The task of the human brain remains what it has always been; that of discovering new data to be analyzed, and of devising new concepts to be tested.”
Naresh Trehan is CMD, Medanta Hospitals. The views expressed are personal