5 Ways Artificial Intelligence Is Completely Transforming The Healthcare Industry

Robby Gupta

In today’s world, the business community just can’t stop talking about Artificial Intelligence (AI). What once was a murmur has become a loud buzz and can be heard reverberating across the corporate corridors. Given the potential of AI and the extent of possibilities associated with it, business strategists all over the world are going pally with it.

Its intervention is conspicuous across the industries and healthcare industry appears to be quite loud in showing its affection for artificial intelligence. One of the numerous data-points that attest to this is an estimate by Global Market Insights which says that the healthcare artificial intelligence market size is expected to rise at 40% CAGR and exceed USD10 billion by 2024, from about USD 750 million in 2016.

AI in healthcare has paced up phenomenally in recent years and is extending its reach in the far corners. Healthcare operations are becoming automated, interactive and smarter and utilization of a huge pool of scattered data has generated extremely valuable insights that have proved instrumental in revamping patient care and public health model, thanks to machine learning and analytics. And now the industry has stepped into the age of cognitive technology.

In this blog, we will read about five major areas where AI is making an unprecedented difference. Let’s go ahead.

  1. 1. Application of virtual Health Assistants

Healthcare organizations invest massively in their customer service and employ an enormous headcount towards it. However, health is an ongoing need and often leaves a lot of gap between the patients and the medical staff. To bridge this gap, providers have started to use virtual health assistants powered by AI.

These digital assistants provide dedicated and on-the-go support to the patients irrespective of their geographical location. The support includes monitoring their health, sending medication reminders, warning them on possible health issues etc.

Chatbot assistance is the next innovative introduction of AI in healthcare. Enabled with machine learning and natural language processing features, the chatbots can understand the contextual meaning of the patients’ input and drive the conversation in a human-like interaction.

The bots are almost a machine substitute of a human support staff, only quicker and evolving with each interaction. They are gradually taking up more responsibilities of the human staff such as responding to health query responses over a chat, email or even a phone call.

Their cognitive capabilities allow them to analyze patient sentiments and raise an alert for a human intervention as and when needed.

As the technology evolves further, it doesn’t look too long before we see the chatbots completely taking over the customer services responsibilities in healthcare.


2. Drug research and development

Drugs and medication have an irreplaceable role in patient care and the success of a treatment. However, drug development is a complex process which requires a long time and massive monetary investment. A new Businessworld article quotes an IBM study result that it can take up to 15 years and USD 2.5 billion to develop a single drug. Isn’t that a monstrous amount of money?

Pharmaceutical companies are looking up to AI to turn drug research and development an easier process.  AI has the ability to leverage tons of unused clinical data to identify symptoms and causes of ailments.

Additionally, they can run tests on a variety of chemical compounds and analyze the results based to determine which one has the traits to treat certain ailments. Needless to say, this can shorten the drug development lifecycle and slash the involved research, testing and development cost phenomenally.

Artificial intelligence in medicine development will give the patients timely access to more effective medicines which would not cost them as much as the previous drugs did. Wouldn’t that be great? Let’s wait for more pharmaceutical companies to start investing in AI. We should have a variety of cheaper and more effective medicines in the market sometime soon.

3. Precision in diagnosis

Efficacy of a treatment heavily depends on the accuracy of diagnosis. Doctors look at the lab results and determine the nature of treatment based on that. However, largely lab tests are still performed by human clinicians and medical staff. This leaves a big room for human-errors.

A single miss noticing a critical symptom can a patient dearly, sadly not only monetarily. These errors can be detrimental and even fatal in serious cases.

Thankfully, AI is acquiring a bigger role in healthcare by stepping into the area of diagnostics. Applying machine learning, more accurate and reliable results can be produced and those details would stand really weak likelihood of going undetected which the eye of a human doctor may possibly miss out on.

With AI, it is possible to create deep-learning algorithms which can help in an early and precise diagnosis and determining the best treatment methods. In the broader picture, AI can be instrumental in improving diagnostic processes, cut down healthcare costs for the patients and reduce the number of fatalities significantly.

4. Home-based and elderly care

Home-based care is another offering of AI which has made the lives easier by making care accessible to the patients from the comfort of their home. In particular, this has turned out be a boon for elderly patients who need frequent assistance and for whom commuting increasingly becomes a challenge.

With the help of wearables, smartphones and connected devices, they can monitor their health and can be automatically reminded of their medication. The sensors can raise an alarm in case of an anomaly so that the timely help is available to them.

Telemedicine has raised the level of convenience in healthcare further up which has brought down the number of visits to the clinics considerably.

5. AI in mental health

According to the World Health Organization, the global economy incurs an annual loss of $1 trillion due to mental health disorders, depression and anxiety being top items on the list. Another study by the UK Mental Health Foundation says that untreated mental health problems contribute 13% of the total size of global health disorders. Despite these shocking figures, mental care is yet to catch up with the overall healthcare delivery.

One major factor of this can be the lack of awareness among people on a global level. Unfortunately, in several countries, there is a considerable number of cases that go undetected and thus untreated. Other reasons are the late detection of ailments, insufficient information, and the scope of human errors.

Machine learning in healthcare is helping to detect the symptoms of a disorder at early stages and restrain its impact. This is proving immensely helpful in following an effective and personalized course of treatment and providing the most appropriate patient care. It’s turning out to be even more helpful for the patients who have difficulty in opening up and sharing their problems even with the trained consultants, only to make it worse for their health.


The Midas touch of technology is transforming the shape of the healthcare sector by the day. AI is all set to revolutionize all the aspects of care, right from running basic tests to determining appropriate treatments to curing the once incurable diseases. It is redefining the patient care and upgrading the courses of treatment by removing all the barriers to an effective care delivery.

This Midas touch is here to stay and turn numerous other processes on its way into gold. Although AI may not be an elixir for patients, at least for now, it surely has the potential to find where to find it.


about the author

Robby Gupta

Robby Gupta is the head of US operations for TechJini, Inc. He has had varied experiences working in New York, Cupertino, and Bangalore with packaged & amp; custom web and mobile app development for an assortment of industries. His current focus is Immersive Technologies, IoT, AI bots and their applications in the digital enterprise.