Ross Upton, CEO and Academic co-founder of Ultromics discusses how Artificial Intelligence will provide increasingly needed help to clinicians in diagnosing complex cases of heart disease.

 

Coronary heart disease (CAD), is the world’s leading cause of death, claiming 9.43m lives a year. The British Heart Foundation states 2.3m people in the UK are living with CAD which results in 66,000 deaths every year, or one death almost every eight minutes.

This is a serious problem that needs an innovative solution – and developments in medical diagnostic technology could provide the answer. Artificial Intelligence (AI) has the potential to help clinicians identify CAD earlier and more accurately. This enables more effective disease management and treatment, enabling people who suffer from heart problems to live better, fuller, longer lives.

There are over 60,000 echocardiograms carried out every year to try and diagnose CAD. When analysing an echocardiogram, a clinician looks for certain factors that indicate the presence of the disease. More often than not, this process does not take into account data points that are invisible to the naked eye and, unfortunately, misdiagnosis of CAD occurs in one in five patients.

A misdiagnosis can be life-threatening if a patient with a fatal condition is sent home or operated on based on an inaccurate diagnosis. It also wastes time and money on incorrect treatment and management – for both the patient and the healthcare system.

However, machine learning algorithms can shed more light on the invisible data points which cannot be seen by the naked eye in echocardiograms, bolstering the clinician’s analysis and leading to a more accurate diagnosis.

 

AI: lending a digital hand

The medical community is no stranger to AI. This advancing technology is heralded for its potential applications in all areas of healthcare; from diagnostics to medication and nursing care; however, the potential for AI in cardiovascular diagnosis provides a clear look at all the benefits.

MedTech innovations, such as EchoGo, the world’s first AI-based, ultrasound diagnostic support tool for CAD, reveal far deeper levels of information buried within echocardiograms. It does this by using machine learning algorithms which draw on one of the world’s largest imaging databases. The algorithms use the database to analyse thousands of data points in each echocardiogram. This generates a more accurate representation of patient outcome based on historical data. As a result, this technology provides a much more accurate diagnosis.

This improved diagnostic accuracy for CAD could quite literally save thousands of lives – as well as millions of pounds. A patient that is accurately diagnosed does not have to endure the physical and financial false-starts that often accompany an incorrect treatment plan.

It’s important to emphasise that this AI-based technology in no way supplants the clinician’s role. Rather, it augments their medical expertise, enabling them to provide a far more effective diagnosis and treatment plan. The sooner a patient is on course with the right plan, the better able they are to manage their heart condition – freeing up doctors and specialists to tend to other patients.

Nonetheless, there is a lot of discussion around AI and its potential to replace doctors. The reality is that MedTech advances such as EchoGo can help clinicians provide better care, without having to make any change to existing workflows. Doctors stand to gain rather than lose by using advancing technology like this.

Looking ahead, advances in software could see physical health tech products getting smaller and smaller. This means diagnostic software could soon feature in devices small enough to fit into a patient’s hand, such as smartphones. Patients can take far more control of their health, where first line diagnosis can be looked at in the home rather than having to go into the hospital to identify the problem. The data can then be shared immediately with the doctor, fast-tracking the correct line of treatment.

 

Identification, treatment and prevention

More accurate CAD diagnosis does not only mean more effective treatment. Its benefits reach even further and can potentially stop the disease from accelerating into a major medical problem. Early identification is key.

The current broader clinical emphasis is on trying to stop the well-established and difficult-to-manage disease in older patients. This reactive approach costs huge amounts of money and takes time. Proactive healthcare providers could use AI-augmented diagnostics and monitoring tools to focus on maintaining cardiovascular health in younger people. With enough hospitals and clinicians adopting such an approach, we could significantly stem the tide of heart disease.

Advancing technologies like AI diagnostics offer medical benefits for both the healthcare sector as well as its patients. Accurate and early diagnosis is key to saving lives and reducing costs. With that in mind, any reluctance needs to be overcome.