The potential of artificial intelligence (AI) to transform every sector is no more a myth. Alike every industry churning to unearth the best out of this novel technology, healthcare industry is said to be the earliest industry taking benefits of AI. From the last few years, AI has showcased major growth, and due to the pandemic we have seen a major boom in this segment. Overall, the growth of AI in healthcare industry has marked an unbelievable growth. Today doctors have been solving cases and even diagnosing major diseases through the vital power of AI. Technology and specifically AI has made everything possible, handling patients while following the social distancing or taking doctor prescription remotely is only a few steps ahead. The acceptance of AI in healthcare industry is slowly catching the pace. According to a report by ResearchandMarkets, the applications of artificial intelligence in the healthcare space will be worth Rs.431.97 Bn by 2021.
The market condition says that the healthcare industry will see tremendous growth in coming time. There are few major challenges, like: handling medical procedures, high-quality services, training doctors, etc. which are going to be sorted soon. While focusing on the same Nitisha from BISinfotech catch-up with Chaith Kondragunta, CEO, AIRA Matrix; Dr.Manjiri Bakre, CEO and Founder, OncoStem Diagnostics Pvt Ltd; Raj Janapareddy, Founder & CSO, Healpha; Raktim Chattopadhay, Founder and CEO, Esperer Nutrition (EON) and Sigal Atzmon, Founder & CEO, Medix Global.
Importance of AI in healthcare industry
While highlighting the importance of artificial intelligence in healthcare industry, Chaith says AI technologies are transforming from being evolutionary to becoming more revolutionary. AI is now able to identify patterns in healthcare data that are not apparent to the human observer, and can predict outcomes that surpass the computational ability of the human brain. This has already opened new paradigms in precision diagnostics and personalised medicine.
“Deep/Machine Learning-based solutions are now being increasingly applied in screening and triaging for effective primary care, in decision support systems for disease diagnosis and prognostication, for prediction of disease progression, to enable personalised therapy regimens, assist in robotic surgeries and as virtual nursing assistants to help post-operative care. Artificial Intelligence is helping make delivery more efficient and personalised with improved healthcare outcomes”, he added.
AI has been successfully and effectively used in area of radiology which has its implications in diagnosis/detection/prediction of diseases related to neurology, cardiology, cancer etc. The role of AI is significant and far-reaching for a complex disease like cancer. This technology has found its place in different domains of cancer like screening, detection, diagnosis, and prognosis, explained Manjiri.
Raj shared the usages’ of AI in healthcare industry. He says, I personally see artificial intelligence being used in the entire healthcare life cycle management. Some of the key areas Dx, Tx, Rx and in discovery of tests, medicines, vaccines and treatments.
AI is becoming more sophisticated at doing what humans do, but more efficiently, faster, and for less money. Both AI and robotics have enormous potential in healthcare. AI and robotics are increasingly a component of our healthcare eco-system, just as they are in our daily lives, said Raktim.
Whereas Sigal says that AI is effective in areas of early detection, diagnosis, treatment, prediction and prognosis evaluation in diseases such as cancer, neurology and cardiology. Through application of big data analytics, one can gather relevant information from piles of healthcare data, such insight can assist in clinical decisions. For e.g. Zebra-Med’s AI1™platform is integrated with Apollo Radiology International’s dedicated COVID Reporting Center that reviews and analyzes all CT scans received across Apollo Hospitals around India.
Challenges & Scopes
The digital transformation in healthcare sector is not as easy as another sector. The main issue is with the processing data and analysis. All clinics or hospitals have a numerous amount of data and for handling those data, we should have robust AI systems.
Chaith agrees with our point, he says Deep Learning-based solutions typically need to train on vast amounts of annotated data. Availability of such data sets for training is a huge challenge in the development of Artificial Intelligence solutions.
Ensuring heterogeneity in patient data in terms of age, gender, sexual orientation, ethnicity, geography, genetics, etc. in the training data is essential to develop an algorithm that gives unbiased outputs and is universally applicable. Collating this kind of variable data can prove to be a daunting task.
While focusing on security issues, Manjiri explained that accessing personal medical records of patients is strictly protected. In recent years data sharing between hospitals and AI companies has generated controversy, highlighting several ethical questions. Patient privacy and the ethics of data ownership is a major challenge for AI in healthcare.
There is another challenge of software bugs, while testing the patients quality assurance going to play huge role.
So, introducing a website for medical products that is negatively affect than the image of companies that produce them as well as the medical professionals, hospitals, and patients are going to be ruined.
Raktim clarified it and said, the pressure is going to be double on healthcare systems and equipments. Integration and legal challenges can be taken.
While sharing the scope of AI in healthcare industry, Sigal shared that at present, India faces many challenges when it comes to the distribution of healthcare. A dearth of clinicians, inadequate infrastructure, insufficient government investment, high-treatment costs, weak doctor-patient ratio, late diagnosis, overworked doctors and ailment unawareness are some of the problems. According to World Bank, nearly two-thirds of India’s population lives in rural areas but is served by one-third of the country’s doctors. This statistic has further encouraged innovative companies to use AI to remedy the shortfall by helping low-skilled health workers diagnose medical conditions.
Raj also agreed with Sigal, he says artificial intelligence is already being embraced and I foresee that it will be an integral component of healthcare. This will enable us to provide universal healthcare to all, especially the underserved and unreached.
Sigal adds, the government is also trying to create a national digital health infrastructure, which has introduced multiple entities for specific functions. Some of these include a ‘Healthlocker’ – an electronic national health registry and cloud-based data storage system that would serve as a single source of health data for the nation. Also introduced was a federated personal health records (PHR) framework that would allow data to be available both to citizens and for medical research. There is also a coverage and claims platform that would support large health protection schemes, a national health analytics platform and a unique digital health ID for each citizen.
Future of AI in Healthcare Industry
The transformation of healthcare industry can be seen widely by us as it has drastically improved. The advance machine, applications and other technologies have made our each medication work quite easier.
While explaining the transformation Chaith says, AI holds the promise of playing a significant role in disease prevention – by predicting disease and its progression path, before the symptoms fully manifest. This opens a proactive approach to disease prevention and healthcare. In the near future, AI applications can also help translate intelligence gained from the ‘gold standard’ but invasive diagnostic procedures like histopathological examination of biopsies to improve performance of less accurate but non-invasive procedures like radiology imaging. This type of AI applications provides the promise of easing the procedural burden on the patient, reducing patient morbidity and making healthcare diagnostics cost effective.
Manjiri says, the best opportunities for AI in healthcare over the next few years are hybrid models, where clinicians are supported in diagnosis, treatment planning, and identifying risk factors, but retain ultimate responsibility for the patient’s care. This will result in faster adoption by healthcare providers by mitigating perceived risk and start to deliver measurable improvements in patient outcomes and operational efficiency at scale.
AI can transform healthcare and health delivery completely. It will be virtual, real-time, on-line and most importantly frictionless. Thereby, providing universal healthcare accessible and affordable to anyone, anywhere, anytime. Patients would consume healthcare like OTT channels i.e. at their own time, own space, own pace, own language, own preference, clarified Raj.
In the complex and evolving field of medical science, doctors would have the last word, not AI. It’s a value-add, an enabler and an assistive guide to medical doctors to efficiently run the healthcare system and achieve better patient outcomes. Considering the healthcare demands of a young population, aging demography and the Indian middle class, AI portends a healthy prognosis, added Sigal.
AI offerings for Healthcare Industry
AIRA Matrix provides AI-driven solutions that aid predictive medicine, precision diagnostics and personalised healthcare. These solutions are focused on two areas: Cancer Diagnostics and Ophthalmology. In the Cancer diagnostics space, the solutions aid screening, diagnosis, risk stratification and prediction, in prostate and lung cancer. As an example, AIRA Matrix’s solution for prostate cancer helps in effective risk stratification of patients at the outset, ensuring that morbidity and mortality due to over and under diagnosis of prostate cancer are reduced. This helps physicians visualise the course of the disease and effectively tailor treatment, in line with the projected trajectory. In the Ophthalmology space, they provide solutions for screening and point of care diagnosis of common blindness causing diseases, also grading and monitoring them. Its predictive analytics project in this area, is aimed at developing a solution for predicting the onset of neuro-degenerative disorders (Alzheimer’s disease, Parkinsonism, etc.) based on non- invasive modalities like retinal scans.
OncoStem’s mission is to provide precise prognostic solutions to cancer patients minimizing the serious side-effects of unnecessary therapies like chemotherapy. Towards this goal they have launched its flagship product ‘CanAssist Breast’ (CAB) that helps to personalize treatment for woman diagnosed with early stage breast cancer. CAB uses immunohistochemistry technique and artificial intelligence to assess the need of chemotherapy in HR+ HER2-ve early breast cancer patients. CAB predicts the ‘risk of cancer recurrence’ in 5 years from diagnosis for eligible patient, based on which treatment is planned, if the risk is ‘low’ patient can ‘avoid’ chemotherapy and if risk is ‘high’ patients will ‘need/benefit from’ chemotherapy. CAB is an advanced biomarker-based test performed on patient’s tumor samples in OncoStem’s central NABL, CAP accredited laboratory in Bangalore. CAB helps to reduce ‘overtreatment’ in hormone receptor positive early-stage breast cancer patients with chemotherapy.
Healpha is a connected healthcare solution providing 360 degree care encompassing Preventive, Curative and Managed care. They use AI for various applications such as: Detection and diagnosis, Treatment, Prescription, Voice / Speech, Virtual assistants and Bots in health delivery. AI has enabled Healpha to save 10s of thousands of people from overcoming blindness, deafness, ENT and other ailments.
Esperer is evaluating research based scientific nutrition on an ongoing basis and aspires to become the pioneer in customised, personalised nutrition which can be made available to the person with entry of a few data points and at the click of a button.
The focus at Medix is that we see AI and data driven healthcare as an important element of the eco-system which will enable to tailor solutions while streamlining processes and making healthcare provision more efficient.
The biggest issue of patients in countries like India is where to go for and get in touch with the best available doctor and services.
Medix has a global network of over 4,000 specialists and 2,000 leading hospitals, besides 400 plus in-house doctors alongside nurses, medical admin and research teams. It’s AI and digital health tools can connect a patient to the best doctor across the globe. Medix service offerings slightly depend upon the market, but its range of services includes: personal medical case management; disease prevention management services; medical concierge & medical tourism, digital health & AI driven solutions; services for high mobility employees; home care, clinical strategy and medical governance services.