Artificial Intelligence offers a great opportunity for better healthcare in countries like India and other developing countries around the world
This is an exclusive article series conducted by the Editor Team of CIO News with Saiprasad Muzumdar, former CTO for India for one of the large UK banks
About Saiprasad Muzumdar:
Saiprasad Muzumdar is the former CTO for India for one of the large UK banks. He is passionate about providing technological solutions for the betterment of human life.
Artificial Intelligence (AI) has become a buzzword in the field of technology as well as in user domains. With the release of ChatGPT at the end of last year, conversational AI has become a point of conversation across the CXO tables, with everyone eager to talk about it.
Contrary to popular belief, artificial intelligence (AI) is not one technology but rather a collection of them. Most of these technologies have immediate relevance to many of the day-to-day processes and applications that we use. One of the key applications I foresee is in the field of healthcare. More so in India, where, as per a 2020 report by the World Health Organisation (WHO), the density of physicians is 0.7 per 1000 population, compared to WHO stated norms of at least 1 per 1000 population, and much less compared to Europe, where it averages around 4 per 1000 population and in the USA, 2.6 per 1000 population. The issue is more pronounced in rural India, where the ratio of physicians and especially specialists is abysmally low, resulting in poor healthcare for the citizens. There is no silver bullet to increase the physician-population ratio in the short term. This is where artificial intelligence can help bridge the gap. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. I am trying to give a glimpse of where artificial intelligence can help. I have also raised some of the ethical issues faced in the application of artificial intelligence to healthcare.
Some particular AI technologies are very relevant to healthcare.
Machine learning: neural networks and deep learning
In healthcare, the most common application of traditional machine learning can be precision medicine—predicting what treatment protocols are likely to succeed on a patient based on various parameters and the treatment context. This could be a great help in primary health care centres across the country in the absence of specialist doctors.
The most complex forms of machine learning involve deep learning, or neural network models with many levels of features or variables that predict outcomes. A common application of deep learning in healthcare is the recognition of potentially cancerous lesions in radiology images, which can help in early detection and treatment.
Natural language processing
Natural Language Processing (NLP) systems can analyse unstructured clinical notes on patients, prepare reports (e.g., on radiology examinations), transcribe patient interactions, and conduct conversational AI.
Rule-based expert systems
Expert systems based on collections of ‘if-then’ rules have been the dominant technology for artificial intelligence and are widely used commercially. In healthcare, they can be widely employed for ‘clinical decision support’ purposes. They are slowly being replaced in healthcare by more approaches based on data and machine learning algorithms.
Physical robots
Surgical robots provide ‘superpowers’ to surgeons, improving their ability to see, create precise and minimally invasive incisions, stitch wounds, and significantly increase the productivity of a surgeon. Important decisions are still made by human surgeons, however. Common surgical procedures using robotic surgery include gynaecological surgery, prostate surgery, and head and neck surgery. In a country where the number of surgeons is far lower and extremely overloaded with the number of operations to be carried out, this can be a great boon.
Robotic process automation
In healthcare, they are used for repetitive tasks like prior authorization, updating patient records, or billing, allowing the health care system to reduce mundane administrative tasks, delay paperwork, and focus more on the treatment of patients.
Ethical implications
There will be ethical implications around the use of artificial intelligence in healthcare. Healthcare decisions have been made exclusively by humans in the past, and the use of smart machines to make or assist with them raises issues of accountability, transparency, permission, and privacy. No doubt AI systems will make mistakes in patient diagnosis and treatment, and it will be difficult to establish accountability for them. Should the onus of the mistake be on the AI system and its creator, or on the doctors treating the patient? That will be the proverbial million-dollar question and may lead to legal action. Machine learning systems in healthcare may also be subject to algorithmic bias, resulting in wrong predictions on the basis of gender or race when those are not actually causal factors.
Conclusion
Artificial intelligence offers a great opportunity for better healthcare in countries like India and other developing countries around the world where physician density is low. It can complement and supplement the existing healthcare experts and make quality and affordable healthcare available across the nation. This in turn provides a great business opportunity for established software product companies and start-ups alike to come up with innovative artificial intelligence -based healthcare solutions.
Also read: How I use GenAI tools as a CTO?
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