Heartificial Intelligence

Artificial intelligence is reshaping the business landscape of industry and Healthcare is not an exception. Various ways in which this is going to happen probably faster than what we would ever imagine.  Recently I have embarked on a learning journey as part of my organization’s, the Machine Learning, Deep Learning/Neural Network, Data Science, Robotics have a huge potential application in the industry. Healthcare Artificial Intelligence, let me brand it as Heartificial intelligence, is posed to reduce the time of new product lifecycles and lower R&D spends. Here are the major areas in which Heartificial Intelligence could become a game-changer in the Healthcare industry.

Diagnostic:  You might have seen the viral video by Google AI’s retina scanning that could advance diagnosis not only eye-related but also cardiovascular disease. Sundar Pichai explains that deep learning makes this possible. AI is going to augment our ability to diagnose diseases. There is a lot of machine learning in progress that will make this possible (Link to Sunders Video: https://www.linkedin.com/feed/update/urn:li:activity:6567069791461441536)

Digital twins: If it is about self-driving cars in automobiles, in healthcare it is about digital twins that resemble a clinical study. One of the interesting areas in which Digital Twins can immensely benefit in the healthcare industry is new product testing before launch. Currently, a new drug takes about 10 years to come to the market and the majority of the time is consumed to test it in various iterative dimensions like Invitro, followed by animal models and then humans. But InSilico Target Discovery, Toxicity Prediction, Compliance Monitoring, identify biomarkers are some of the areas where we have already seen the application. A predictive twin model could be the next leap in accelerating the new product ‘time to market.’

Open Source movement in Healthcare: In software when everything used to be the property of individual companies,  the growth was sluggish and expensive.  But once the free source movement started, that helped unprecedented growth of the computing and mobile industry. In Healthcare today our operating model is a proprietorship model.  Every single company does its own clinical trials for every single drug, every single time and generates its own database. The free source movement in Pharma could also put its growth curve in unprecedented uncharted areas that could take up the industry to the next level. AI and related technologies need tons of data to be predictive. Data sharing between businesses is a vital first step for this.  The areas where I am seeing the applications are the precise selection of treatment, and outcomes targeting of drugs for diseases based on the Global database, Shared clinical data that could reduce the number of subjects and patients required to prove a drug is safe and effective.  

Digital Consultation: To combat COVID and its spread, many governance and health authorities used ‘Apps”. COVIDsafe of Australia, HaMagen of Israel, BlueSafe, SwissCOVID, ArogyaSethu in India, there are several apps that are used for tracking as well as self-diagnosis of the disease.  This is the tip of the Iceberg of the diagnostic process. In the future this might get expanded to improved diagnosis, combating the spread of transmissible diseases and precise specialized treatment. As a piece of sidebar information, India’s Aarogya Setu became the world’s fastest-growing application, beating Pokemon Go. 

Employment Neutral: A McKinsey survey indicated about 800 million jobs will become obsolete by 2030 due to artificial intelligence. At the same time, there are other reports that conclude that about 300-800 million jobs will be created due to AI and related technologies.  Healthcare is a sector where it is said to be having a lower impact.  but at least it will be neutral when it comes to the Employment aspects. However, this would result in a shift in the type of skillset, toolset, and mindset.

Photo by Franck V at Unsplash

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