Advancements in today’s world are a result of interdisciplinary research across various fields of science and technology, and Artificial intelligence (AI) is playing a significant role in shaping today’s research. The power of AI in healthcare lies in its ability to process and make sense of an enormous amount of data in a considerably short amount of time.  

The use of AI in healthcare has various applications ranging from getting a better understanding of human biology at a genetic level to maintaining patient data to increase the hospital’s functioning for efficiently understanding a person's emotional state. AI is reforming and shaping modern healthcare through algorithms and devices that can forecast, assimilate and take the required action. AI is actively being used across various areas of healthcare such as medical imaging, wearable sensors, guiding surgical robots, etc.  

According to NASSCOM (National Association of Software and Service Companies), data and AI in healthcare have the potential to add about 25 billion dollars to India’s GDP by 2025.  

What’s in store? 

AI for a database of outbreaks 

Many initiatives are being taken by the government and various private organizations to better utilize AI to benefit the medical sector in India. A tool is currently being developed by a private company in collaboration with the National Centre for Disease Control (NCDC) that will scan all media reports related to health, to create a database of outbreaks of 33 diseases, some with the potential to become epidemics, that are monitored under the Integrated Disease Surveillance Programme (IDSP). Another Indian company called Deeptek.ai is also working on a project that uses AI in radiology for TB screening. It can be helpful in a country like India, where the number of radiologists is scarce.  

AI for diabetes and eye care 

Many projects under NITI Aayog are also working on collaborating AI with healthcare for the early detection of diabetes complications and validating the use of AI as a screening tool in eye care. It will expand the capacity for eye screenings and early detection and enable access in remote areas across the country. 

AI in mental health disorders and Autism 

AI is also actively used in reading, monitoring, and interpreting the emotions of a human being. Emotion AI combined with video conferencing helps autistic individuals to communicate effectively with the people around them, enabling them to understand their emotions better. Emotion AI software can effectively use voice analysis to assist clinicians with diagnosing various mental diseases such as depression and dementia. This application of Emotion AI is also beneficial during pregnancy care, where it can be used to study the emotional status of pregnant women and take timely action to help them deal with the mental issues afflicting them. Emotion AI technology is helpful in in-patient care for the elderly. It is used to remind older patients with long-term treatment regimens to take their medications on time and monitor their overall well-being.  

AI in Oncology  

AI has a vast range of applications in oncology as well. At OncoStem, we are working towards integrating AI with oncology to understand the prognosis of a tumor. OncoStem’s motto is to move away from the “one size fits all” approach. The company’s flagship product, CanAssist Breast (CAB), helps to personalize treatment for women diagnosed with breast cancer. CAB uses AI to give the probability of cancer recurrence for each patient, based on which treatment planning takes place by the clinician. OncoStem diagnostics is also working towards the development of prognostic tests for various other types of cancers such as Triple-negative breast cancer and Ovarian cancer using AI to analyze the patterns of over and under-expression of specific genes involved in tumor progression.  

AI in predicting the risk of heart attack 

Microsoft’s AI Network for Healthcare collaboration with Apollo Hospitals is developing a machine learning model for enhancing the prediction of a heart attack. AI solutions can identify new risk factors, utilizing clinical data from over 400,000 patients, and can provide a heart risk score to patients without a detailed health check-up, enabling early disease detection.  

Although many initiatives and projects are taken up to make the best use of AI to help the healthcare sector grow, there are a few key hurdles that one must keep in mind such as the need for a large amount of accurate data. Patient data should not be exploited and used without informed consent. Patients should be made aware of how their data can be used to train AI-based algorithms and models to improve QoL.  

There is a long road ahead to make the best use of AI to benefit the healthcare sector. Schemes such as NITI Aayog should encourage collaboration between the public and private healthcare sectors to ensure that all the available resources are utilized to their full potential.  

With all the private organizations and government-led initiatives, the upcoming trends of AI in healthcare look bright in the coming year. 

Photo by Angiola Harry on Unsplash