How Big Data and AI is Disrupting the HealthIT

Despite the fact that our brain has got immense storage and processing power, we prefer storing our data on digital space. In consequence, the digital data is enlarging in size and is estimated to reach 44 trillion GB by 2020. Surely, such big data is impossible for humans to handle and thus Artificial Intelligence (AI) would be needed to track, manage, and probably, process it as well.

While ‘real’ AI is a near future, we have started to use the best of narrow AI in the form of self-driving cars, search engines, security surveillance, and other devices. Similarly, we could see a number of potential implications of AI in healthcare that showcase an optimistic future of diagnosis, curing, and delivery of care. Let’s peek into some of the revolutionizing examples in healthcare that are surely disrupting the industry and leading the way to more inventive solutions.

a. Mining Medical Records for Treatment Plans  

One of the most apparent applications of AI in healthcare is data management. Gathering, storing, and normalizing data is the primary step in transforming the existing system of care. We could see this job being done phenomenally by the Google Deepmind Health project, that mines the medical big data to render better solutions.

Every test or scan conducted on a patient comprises of a set of information, indicating if the patient is at risk or what are the decisive steps in treatment. If this information (in the form of big data) is available, it can assist hospitals and physicians to save lives. In order to sort this data and offer relevant suggestions/solutions, AI helps. Instead of programming the systems to recognize the potential symptoms or signs of a problem, AI systems are trained to interpret the data into significant results. This would enable doctors to learn the issue and provide efficient treatment possible.

Currently, this deep learning research is being deployed for eye scans at Moorfields, and head/neck scans at University College London Hospitals. The issues are recorded, stored, and are sorted to recommend the right course of action to the clinicians.

b. Assisting Physicians in Performing Repetitive Tasks

Cognitive assistance, another application of AI has been aiding the HealthIT with analytical and reasoning capabilities. One of the potential and active examples of this is Medical Sieve, which aims to simplify decision making in cardiology and radiology. The project under IBM will analyze the radiology images (based on cognitive learning) and will spot and detect the issues, faster. This will consequently spare the radiologists from handling minor cases and have their focus on complicated cases either, where human supervision holds more significance.

c. Diminishing the In-Person Consultation Gap 

Suppose you have headache, you feel dizzy, but you are uncertain about the malady. You need to visit the doctor but you get the appointment after two days. Now that’s where AI is filling the gap.

There are apps like Babylon that are making in-person and online consultation easy. Backed with AI, the apps let the users report the symptoms of illness, which is then checked against the database of disease through speech recognition. Once the history of the patient is analyzed along with the current circumstances, Babylon offers relevant recommendation to them. Together with this, the app also reminds the patients for mediation, follow ups, and change in the course of action, accordingly. Such apps are programmed with Machine Learning (ML) to understand issues confronted by varied patients, studies them, and use this database for relevant suggestions. And with such examples, we can have  some reasons to justify that mobile applications in healthcare are making for new opportunities and innovations.

d. Advancing Genomics for Healthier, Longer Living

AI is immensely impacting genetics and genomics. Take example of Deep Genomics, which analyzes the data patterns of genetic information and medical records so sa to verify the variations and linkages to a disease. With this, a new generation of computational technologies is introduced that will let the geneticists, predict what will happen within a cell when a DNA is undergoes any genetic variation, either natural or therapeutic.

In similar context, Craig Venter, an American geneticists is working on an algorithm that could design physical characteristics of a patient, based on their DNA. As an extension to his work, he has his enterprise, known as Human Longevity Inc. The scientists at HLI have created the largest database of sequenced genomes and phenotypic data, that can enable spotting cancer or other vascular disease at an early stage.  

e. Drug Creation 

Clinical trials for developing pharmaceuticals is a long process, which can sometimes take a decade or more and even cost million dollars. To make his process cost-effective and ascertain that innovation reaches the healthcare industry as fast as possible (especially in epidemic), AI has been making some amazing contributions.

One of the popular example of this one is Atomwise, which uses supercomputers for examining the database of molecular structure to find relevant therapies. Atomwise has made use of virtual search in the past to look out for safe and existing medicine to lessen down the effect of Ebola virus. The drugs suggested by the AI technology proved to have offered positive effects in just one day, which could have otherwise taken months or years.

ALSO READ: Major Challenges in Healthcare Application Development

How is AI Defining the Future of Healthcare?

At first, Artificial Intelligence had to breakdown the prejudices and fears that were linked with its potential and involvement in a critical domain like healthcare. However, with the examples discussed above, AI is surely manifesting its significance and real time applications in maintenance, diagnosis, and treatment. In the following time, we can certainly have some interesting innovations in the domain through healthcare mobile app development and will have huge medical discoveries happening, backed and managed by AI.