AI/ML fuelling a future of better care and better health

by April 24, 2020 3 comments

Increased affinity for having automated, affordable, accessible, efficient healthcare systems is making AI a key part of healthcare R&D divisions. From robotics to 3D printing and deep-tech to AR/VR simulations — AI/ML is helping build sophisticated solutions, according to Optum Global Solutions’  Vineet Shukla, Sr. Director—Data Science & Machine Learning and Varun Bahl, Sr. Product Manager.

Getting easy access to affordable and quality healthcare service is a challenge for populations across the globe. Naturally, healthcare organisations have turned to technology to find a solution and establish a collaborative environment that can help people live healthier lives.

A recent study estimated that healthcare Industry is going to spend close to US$36B in the Artificial Intelligence (AI) and Machine Learning (ML) space by 2025, touting it to be the game changer. AI/ML has emerged as the most important emerging technologies contributing towards improving patient care and finding predictive methodologies to identify complex diseases at an early stage. It has the potential to transform health care administration and operations, empowering consumers and enabling an integrated health care delivery model.

Key areas in healthcare that are being transformed by AI

With AI-ML maturing at a rapid pace, organizations are developing solutions to take advantage of its full potential. Here are the four key areas among many others, where healthcare researchers are experimenting and utilising AI/ML.

Healthcare operations

This segment is utilising AI/ML to identify and plug gaps in the overall functioning of healthcare systems. From automating prior-authorization to smart scheduling of appointments, AI/ML systems are helping reduce the cost of healthcare. Tele-medicine is another field which is reaping benefits of AI/ML combined with technologies such as AR/VR to reach the last mile.

Radiology and healthcare imaging

AI/ML’s ability to solve visual task is revolutionizing the space of radiology and healthcare imaging. Today we have sophisticated deep learning-based solutions to detect chronic and life-threatening diseases like tuberculosis and lung cancer among others at an early stage. These solutions are also helping radiologists in areas such as detecting breast cancer using mammograms, diabetes detection using retinopathy, etc.

Precision and Personalized Healthcare

This area is at the forefront of medical advancements. Given the highly data-driven nature of this field, AI/ML solutions are contributing significantly in genetic sequencing, deriving hereditary influence, drug interactions and so on. In the field of precision medicine, technologists are utilizing historical EHR information along with other vital stats to provide a personalized, pre-emptive and proactive diagnosis. Smart devices like fitness bands and smart-watches are also utilizing AI/ML to understand an individual’s health and even take pre-emptive actions.

Drug Analytics

This sector is reaping the benefits of improvements in the Natural Language Processing (NLP), especially in the area of understanding drug-drug interaction. The correlation may seem odd but concepts like transfer learning and domain adaptation enable such cross-utilization of research and technology. New drug discovery is another space where AI/ML is providing amazing results. The famous DSP-1181 molecule, used in drugs for treating OCD was synthesized by an AI solution.

AI impacting patient care

AI has brought in a paradigm shift in the business world by making systems and processes simpler, automated, user-friendly, secure and aware. These factors have generated a lot of interest within the healthcare industry where it is making an impact across Cost, Experience and Outcomes or CEO of health care.

Let us dive deeper into each of these aspects.


As per some recent studies, each patient in the US spends around US$2,500 on administrative costs. In India, WHO estimates, that the cost of universal health care delivery is ~ INR 1713 (US$38) per person/annum, requiring the Indian government to spend 3.8% of the GDP for universalizing healthcare services. Stakeholders across the healthcare spectrum are looking for ways to minimise administrative healthcare costs. One such area is improper payments which, as per a recent study, cost the US government, five per cent of the total US$616.8 billion of healthcare expenditure. Here, healthcare analysts are using AI/ML technology to scan and interpret historical data into real-time actionable insights. Over time, the ML-based systems are expected to relate to this data and provide precise instances to identify fraudulent cases at an early stage.


Healthcare service providers are looking for ways to provide patients the right information in a timely manner and reduce wait times to the lowest. AI/ML can play a crucial role here by using historical data and training systems to interact with patients in a better manner. Let us consider a scenario where a patient gets a prescription for pain. Now if the system is able to suggest the patient with options for nearby pharmacies (chemist) that are currently open to purchase the medicine along with some exercises and food types that will help him/her relieve the pain based on his X-Ray data, current drug usage, allergies and many more parameters it will elevate the patient’s experience to a new high. Similarly if the systems can gather patient data, analyse and even suggest the course of diagnosis, before the doctor approves the same, it will assist doctors to reduce the time spent with patients and thereby reduce the overall patient wait time.,


A recent study by Johns Hopkins revealed that more than 250,000 people in the US die every year because of medical mistakes, making it the third leading cause of death after heart disease and cancer. Whereas, India’s medical error deaths are nearly 5 million a year and can potentially be reduced by 50% with the correct steps taken.

AI and ML can play a big role in helping the physicians, nurses, local care workers and staff in providing efficient and accurate care to the patients. By leveraging data, coordination and decision making can become seamless and swift across departments. It can also increase interoperability while reducing overheads for the healthcare ecosystem. AI/ML tools can also help caregivers and laboratory personnel conduct initial assessments faster and in an accurate manner, thus, helping them to avoid patient deaths with preventive and predictive care.

AI to define the future healthcare offerings

Health care is a very large and attractive field for anyone who wants to use AI to drive improvements and disruptive change in the industry. The increased affinity for having automated, affordable, accessible yet efficient healthcare systems is making AI a key part of healthcare R&D divisions. From robotics to 3D printing and deep-tech to AR/VR simulations — AI/ML is helping build sophisticated solutions in healthcare with the added capability of being explainable. The industry has already started using it to address basic tasks such as patient enquiries, appointment scheduling, online payments to more complex activities like making a recommendation on a patient’s health conditions.

While AI is not a panacea, an AI future does present exciting opportunities for all stakeholders.

3 Comments so far

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  1. Pradeep
    #1 Pradeep 18 May, 2020, 17:06

    A very nice article,covering wide scope of AI/ML on future health care system.

    Reply this comment
  2. Amrita
    #2 Amrita 31 May, 2020, 17:23

    Nice Article, very Informative 👍

    Reply this comment
  3. Madhulata Baid
    #3 Madhulata Baid 2 June, 2020, 12:01

    Very much detailed and informative article providing a nice insight into evolvement of emerging tech into healthcare space.

    Reply this comment