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Role of Digital and AI in Cancer Care

We need faster timelines when we talk of adopting digital and AI in cancer care to aid timely and early diagnosis.


February 7, 2022 1:54:31 pm
Cancer Care Delivery

Digital technology can go a long way in supporting the democratisation of cancer care. it becomes all the more pertinent when we look at the figures. According to the World Health Organisation, India had an estimated 1.16 million new cancer cases in 2018, and one in 10 Indians is predicted to develop cancer during their lifetime. Artificial Intelligence, Machine Learning (that can learn to predict outcomes) can empower doctors and patients, in the journey from diagnosis to treatment.

When it comes to diseases like cancer, it’s as much a data problem as a medical one. In that context, technological initiatives aid us in recognising basic patterns, mapping genes and DNA to determine the efficacy of a particular cancer care pathway. For chronic diseases like cancer, one needs access to experts, not necessarily physical access. Digital tools enable virtual reach addressing geographical and time constraints. This shift to virtual expert access has a profound effect in fields such as oncology. In that sense, a seamless navigation pathway that is aided by digital advancements is making a significant impact in the quality of people’s lives.

We’re already seeing several major changes happening. Firstly, CAD (computer aided diagnosis) is ubiquitous now in screening programs and diagnosis, being done virtually. The second big change is the concept of specialised clinics, where one can expect a same day diagnosis, something that could never be imagined earlier. This means being able to visit the hospital in the morning, get a screening for the biopsy, followed by the diagnosis and the tumour board getting together to offer a treatment pathway, all of it possible on the same day. 

The whole concept of specialised out-patient clinics is significant. Then, we have liquid biopsies, digital pathologies, which actually accelerates the turnaround time, which typically takes weeks and months. The third development is that hospitals are actually trying to reposition themselves, focussing more on specialisation in terms of treatment. Finally, there has to be awareness around symptoms, for example, if a cancer patient has a vomiting episode, what could be the contributing factors?

Meanwhile, companies like GE Healthcare are enabling digital solutions, such as its Edison platform, which deploys and manages advanced applications designed to help achieve greater efficiency, improve patient outcomes and access to care. A lot of factors come together to work smartly to ensure an outcome on the same day, enabling an ecosystem where diverse systems converge to offer solutions.

We need faster timelines when we talk of adopting digital and AI in cancer care to aid timely and early diagnosis. In the next 10 years, it is expected that one in 10 people will have some risk related to cancer. Unfortunately, 70 percent of cases are diagnosed extremely late and 90 percent of these are effectively palliative or end-of-life treatment, despite spending a fortune on a multimodality treatment.

In the ideal scenario, which we can look at becoming a reality sooner than later, the physical touchpoint will be minimised to the initial clinic visit or any specific test. One can go home and wait to hear from the expert, who may be anywhere in the world and can interpret and validate the results by people who are among the finest in the country, before deciding on treatment and diagnosis. There are a lot of technology tools and techniques that enable an information flow across a multitude of space in the oncology ecosystem quite seamlessly.

The good news is that the progress is already underway and the challenge is in making it more broad-based. How can we take what the best hospitals in the world have to offer and go from entry to treatment in a single day? And, while we are immensely capable of putting the system together, the challenge is to replicate this across India.

We see a number of new generation players coming into this healthcare space, making precision healthcare possible. There is an urgent need to integrate data from across healthcare centres in a way that it can help in making good clinical decisions. AI and other tools can give us a basic pattern recognition algorithm to say that, for example, if a particular case has been referred to a certain hospital, it would be possible to look at say, 50 similar cases with similar symptoms and their treatment pathways and outcomes. Today, this particular data set is not available in a ready, readable format. 

So, what we have today is only a tip of the iceberg and at the cusp of offering precise, affordable treatment that cuts across countries, populations and reaches the lowest segments of society. We have a long way to go, but on a positive note, the first steps have already been taken.

(Source: Podcast on Role of Digital and AI in Cancer Care, a part of the campaign Cancer Care Matters in association with GE Healthcare. The panel included R Venkataramanan, Founder and CEO Karkinos and Girish Raghavan, VP GEHC – Edison Platform, GE Healthcare.)

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