Dr Rohit Sharma, Founder & CEO, Zini.ai, talks about how technologies powered by Artificial Intelligence (AI) can bridge the gaps in healthcare delivery, and open up a new avenue in clinical processes.

I tis not a question of Doctors vs Artificial Intelligence (AI), but about the future that medical practitioners are heading into with AI. The stakeholders of the medical community have long worked in silo trying to protect their knowledge and control over the healthcare domain. Fortunately, in the world of free markets and information technology, growth and evolution of all systems cannot be stopped.

For decades now, especially in our country, the 4 Ps - the Provider (the doctor), the Payer (the insurance company), the Patient, and the Policy Maker have all existed in their own isolated domains, always putting the blame on the others for any hitches in the healthcare ecosystem at large. These 4 Ps are interdependent yet there is no dialogue between them nor do they have sufficient knowledge about each other to be able to come together and help the most important P of this ecosystem, i.e the Patient.

Thankfully, technology can help bring these 4 Ps on the same page. Here are some great inventions that already exist and have the potential to make sure genuine healthcare reaches every corner of the country.

SCREENING PATIENTS

The average time from first symptoms to the final diagnosis of tuberculosis is ~60 days, as indicated by studies. With symptom checkers like Zini.ai the symptoms can be identified and understood in a matter of five minutes. With AI powered cough sound analysis engines like Swaasa. ai, we can analyse if lung health is pointing towards a particular kind of pathology. Any multipurpose health worker or Asha worker can be trained to use it. We don’t need a doctor in that remote location.

Taking a second example, the average time to diagnose leprosy is more than 50 days after the first rashes appear. Studies say patients are usually diagnosed on their third visit to a clinic, if they even go to a clinic.

First point of approach is usually the ‘quack’ or best case a local dispensary. A skin lesion analysis engine as developed by Zini.ai and many other startups can easily classify and screen patients into who might need further specialist care and at risk of the disease. Early detection is key here. After 30 days, there is a 33 per cent chance that there will be permanent disability. After 50 days, almost 67 per cent chance.

Let’s talk about avoidable blindness. So many productive citizens lose their eyesight to avoidable causes of blindness. I myself am a victim to this, suffering from Keratoconus that was misdiagnosed by two specialists for a year. Solutions by startups like Logy.ai are able to simply use a smartphone camera and detect if someone is developing a cataract in their lens. Some solutions allow usage of a simple retinoscope which any health technician can operate and the AI engines can report if there is a problem in the retina or not. We can screen millions of people, send them to the right care, in time and save their eyesight. We don’t need doctors to see every report; only an AI engine to classify, detect and redirect patients early on.

DEPLOYING RESOURCES CORRECTLY

A doctor will not have to see non-serious cases that put a load on the system while taking away essential time from those who actually need their time and attention.

Imagine the data collected, the analytics possible for all our Ps mentioned above. Why can’t we allocate resources and funds based on this data collected?

Some regions are having a higher load of gastric problems, as per symptom checkers, health officials may need to check the water table or water supply facilities there. A region with higher than usual tuberculosis cases may require more respiratory health facilities over there.

This is just the screening process. Basic primary healthcare guidance to patients can be given by symptom and sign evaluators.

Guiding patients in the right direction from the very beginning. Instead of Googling their symptoms and asking for advice from ill-informed people in their network, an AI powered engine can guide them in the right direction from the very beginning.

Already AI-powered agents are being used to classify X-rays, CT scans and many other investigation results for faster analysis and helping doctors look deeper into the findings. This is empowering doctors and helping patients on many fronts.

AI IN THE OT

Robotic arms assisted surgeries help doctors perform better knee replacements or laparoscopies today. The robotics arms, not only provide a better 360-degree view inside the body but the AI agents inside the system are also able to identify noise or involuntary movements by the surgeon while performing fine movements, there by only the right movements from the surgeon’s hands are passed on to the patient’s body parts, avoiding any catastrophe or accidental movements during the procedure. Many surgical errors can thus be avoided.

Neuralink, the brainchild of billionaire tech mogul Elon Musk, is a company that invented a fully autonomous robot capable of doing an hour long brain surgery and implant the neural ink device into the pig brain.

To summarise, AI technology is here to stay and grow. It is already working in silos. And in order to maximise our potential and make sure the common man (the Patient) is helped the most, all the other Ps in the healthcare industry must work together to adopt and implement these new age solutions for the betterment of the entire ecosystem.

About the author:

DR RoHIT SHARMA is Medical Doctor, Programmer, Project Manager and Co-Inventor of Zini.ai. He is a healthcare professional who has worked on multiple healthtech projects and has years of experience in this industry. He is also a writer, entrepreneur, factual speaker, researcher and explorer. At his venture, GRAINPAD Pvt Ltd, he and his team work on developing AI-driven solutions for the healthcare domain.