Exact Diagnosis Schemas
Arun believes that any smart healthcare model should be able to track unhealthy living that is on a rapid rise today. Basically, IoT-driven systems should be engineered to detect people’s risk levels of contracting various disorders including lifestyle-related and mental illnesses (Alzheimer’s schizophrenia, depression, and more).
Using smart systems, diagnosis and detection of these disorders can also be accomplished at the patient level after which these are escalated dynamically to concerned specialists for actioning.
“Individuals would then be able to work with their primary care physicians to implement appropriate interventions,” adds Arun.
Yet another illustration of smart diagnosis is a recent research by the University of Texas, USA that employs brain mapping using AI to detect vulnerability to depression. Bastin was generous to throw more light on this case study wherein scientists developed algorithms (with a supercomputer) to find out commonalities in MRI scans, and detect anomalities by analysing data to diagnose depression and anxiety.
“It aims to improve upon previous work by researchers who have studied mental disorders via the relationship between brain function and structure in neuroimaging data.”
Ashissh recommends employment of video conferencing to build up history of the patient at the initial level. This could include interaction with the patients ta a personal level.
After the initial stage, lab reports and organs image reports could be interpreted by specialists virtually. Multiple connected healthcare devices would also collect patient data regularly. After these stages, patients can be educated to monitor their vitals at defined intervals to understand bodily progresses quite early. These would undoubtedly lead to a potential ‘smart revolution’ as far as timely diagnosis of different life-threatening disorders are concerned.
“Our aim is to move from sickcare to healthcare,” emphasises Ashissh.
“Finally, we need compact, multiple devices which should be connected all time so that vitals can be measured consistently.”
Both patients and doctors are empowered with IoT, AI, and ML
One associated myth worth busting now is smart concepts replacing doctors.
“All smart systems are probabilistic models, which means that they only provide the probability of a specific occurrence and individuals should always check with physicians to get a deterministic answer. At the end of the day, patients should use these systems to gain information about their health that is otherwise unavailable to them and use this to have a more focused conversation with their doctors,” states Arun.
With smart systems, patients are technologically empowered to detect and diagnose diseases on their own. Doctors and medical professionals can drive accurately vital healthcare decisions. A big benefit that the latter category gets to enjoy is offloading initial decisions and thereby devote more time towards personally attending to patients.
However, the biggest benefit with IoT-driven smart concepts is a win-win situation for both the rural mass and their doctors.
Bastin exudes optimism, “By combining vast amounts of patient data with artificial intelligence, we’re beginning to be able to predict illnesses before they’ve even developed. If machines can see a life-threatening illness before it strikes, this has the potential to save countless lives.”
“Smart systems could make the general ecosystem more proactive by enabling the rural population seek interventions when they start seeing the symptoms.”, believes Arun.
Smart diagnosis models are practically practical in India, three cheers!
Experts, both medical professionals and IoT engineers (and service providers) think that smart concepts in healthcare are truly practical in India.
“We can see the penetration of wearable devices to monitor our health. Now, these devices not only monitor our health but also stores the data in the cloud which is the right source for all these above tasks. So, it is already in the progress,” signs-off Bastin.
“AI, ML for instance could learn from the symptoms, treatments and outcomes of millions of people for a specific condition and provide insights to the treating physician that would otherwise be difficult to predict as an individual.”, states Arun.
“Add to this the realm of possibilities that IoT provides, from preventative care to post-acute care, and we are looking at a whole new healthcare ecosystem that focuses on patient outcomes while reducing overall cost of treatment,” adds Arun.
Finally, what you need to do is, help our government with smart ideas such that our healthcare jumps from developing to world beating.
Major contributors to the story
|Chief Data Scientist at Bengaluru-based Hash Research Labs
|Founder at Scanbo – Healthcare Concern
|Co-Founder at Bengaluru-based Fedo (a healthcare startup extensively using AI, ML and Natural Language Processing to predict lifestyle diseases)
|Director, Healthcare Business, Solix Technologies
Written by Rahul R, Senior Technical Journalist at EFY.