AI in Healthcare

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Technology is changing how healthcare is being administered in India with artificial intelligence making waves in the sphere

Healthcare is breaking out of silos, becoming increasingly connected, but also increasingly complex. While it poses an opportunity for medical professionals to learn more than before, the enormous amount of medical information can overwhelm the decision-making processes. This is where Artificial Intelligence (AI) systems come in.

The specifics

Data from different sources is fed into a system. With the use of algorithms, programs and systems to simulate human intelligence, AI can analyse big data sets. These can include disease processes, clinical presentations, clinician’s notes and reports from a patient’s file, medical research publications, and clinical-trial outcomes. In a matter of seconds, it can create an actionable gist of all, for a particular clinician or a group to review. Ajit Naryanan, CTO, mfine, Bengaluru explains, “Typical applications in healthcare fall in the categories of diagnosis processes, treatment plan development, drug development, personalized medicine, patient monitoring, process automation, robotic surgery and clinical trials.” For instance, when it comes to the pharmaceutical industry, the technology is being used to curtail lead time. “AI and machine learning uses data sets and algorithms to model various scenarios in the drug discovery process. This modeling is used to arrive at predictive hypothesis much faster than the traditional trial and error method, which results in much shorter time for creating proof of concepts,”  says Suhas Tamras, Global Head, Medical Devices Business Unit, Tata Elxsi, Bengaluru.

AI in healthcare can help to leverage technology to deploy efficient, impactful interventions at exactly the right moment in a patient’s care. “As patients demand more from their providers, and the volume of available data continues to increase at a staggering rate, artificial intelligence can provide insights into diagnostics, care processes, treatment variability, and patient outcomes,” says Dr. Garima Anandani, Clinical Director, QI Spine Clinic, Mumbai, that uses a knowledge management system to diagnose, manage, and prevent pain in the back and neck. Over-diagnosis and its corollary, over-testing, are amongst the most harmful and costly problems in modern healthcare. “This is especially true for spinal disorders where imaging tests (X-rays and MRIs) are heavily overprescribed even though European and American Medical Guidelines strongly recommend against it. Function should always be tested first and only those cases that test negative on function should be tested for structure. This is the practice advocated and followed in most branches of medical practice. The danger with over-testing of structure without function is that it often leads to unnecessary treatment or surgery even if the structural deformity is not the real cause of pain or functional disability,” adds Anuj Arenja – Managing Director & Chief Executive Officer QI Spine Clinic. There are broadly two types of medical tests- those that test for function of the organ and those that test for structure (imaging tests). The test for function should always be done first. If the dysfunction is not severe, functional treatment should be tried, if this fails or if the functional disability is severe, then an imaging test for structure should be prescribed.

Changing dynamics

Some important aspects of computational systems is that they can perform repetitive tasks without feeling bored or fatigued and can analyze billions of data bytes in a matter of seconds. “Now if we train such systems to seek specific information in such huge piles of data and throw up results, it can be done easily. Further, if we can grade and qualify such information. It may not be as intuitive as a human, but it can be precise,” says Arindam Haldar, CEO, SRL Diagnostics, Gurgaon. AI systems can bring in better standardisation of processes, and therefore subjectivity in interpreting information will be reduced. There are AI systems already in operation that have demonstrated the ability to identify sight-threatening conditions with equal accuracy to human ophthalmologists. There are those which can scan a human chest X-Ray faster than a medical professional can and detect a small tumor or an early onset of pneumonia. Some trained neural networks can interpret pathology images of tumors at a success rate of detection upwards of 90%, compared to an expert pathologist. AI-assisted Robotic Surgery where robots are able to analyze pre-op medical data and guide a surgeon’s instrument during surgery ensures patients develop fewer complications than otherwise.

Accessibility matters

The biggest impact of using AI is that it can significantly improve efficiency while reducing wastage and costs. In a resource-constrained environment with a low doctor to patient ratio, AI has the potential to deliver remote medicine and create virtual access in an effective manner. This does not mean the doctor will be eliminated. It just means that it will be an aid for the doctor. “Doctors with AI can treat and monitor patients across geographies. Healthcare organizations, whether state or private, can plan policies, guidelines, strategies and infrastructure to address health needs in a precise manner thereby optimising the resources and delivery. The State can prioritize plans, budgetary allotments with greater understanding and in optimal utilization,” says Hanumanth Rao Chitipothu, Co-Founder and CEO, HealthSignz, Bengaluru that calls itself a health intelligence platform using AI. Over 2.5 quintillion bytes of data is generated every minute, which is used by businesses across to generate and deliver accurate personalised services and results. In healthcare, there are endless possibilities to leverage this data generated to make precise predictions. An aspect to be considered is over-diagnosis and Chitipothu says, “AI when powered by the right algorithms can make accurate diagnosis allowing doctors to gain the right insights to suggest the appropriate treatment.” According to experts, machine learning algorithms can make accurate diagnosis 87% of the time that when combined with deep learning can touch around 97-98% success rate. “The auto diagnosis tool is an AI powered tool that runs on actual diagnostic tests results and provides probable risks factors. Additionally, it also suggests users to change their lifestyle by recommending diet and exercise plans. Further investigations (if any) and a list of repetitive examinations for regular health tracking and monitoring is also suggested,” says Deepak Sahni, Founder and CEO of Healthians.com, Gurgaon that offers testing at home.

MHealth

Mobile health or MHealth involves using mobile hardware and software platforms to capture, transmit and view healthcare data. It is an all-inclusive, real time, round the clock approach for healthcare that targets connectivity to every player in the industry. The constant innovation and ever increasing connectivity makes it the most convenient, real-time and efficient way to reach every individual across geographies to deliver top-notch healthcare. The recently launched iWatch is an example of mHealth, which has the capabilities to display person’s ECG in real time. Broadly mobile devices are used for education and awareness, data gathering, remote diagnostics, remote monitoring as well as delivery of care itself through forms of telemedicine. Clinical delivery, Patient progress and feedback are monitored in real time through the use of mobile devices allowing for more stringent control over course corrections and clinical outcomes.

This story first appeared in The Hindu Metro Plus dated 20th Nov 2018 here:

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