AI in Healthcare - A Brief Overview

AI in Healthcare- A Brief Overview
One of the most booming technologies in the 21st century is Artificial Intelligence that has already become a part of our daily life. From virtual assistants like Siri and Alexa to facial recognition in mobile phones as well as airports, Artificial Intelligence is increasingly prevalent in many sectors such as businesses, healthcare, administrative and social.
A number of research projects suggest that AI can perform better than humans at pivotal healthcare tasks such as diagnosing diseases, getting the right medical history, evaluating large data, etc. Through the use of algorithms and deep learning, AI has achieved some success in outperforming medical professionals but it will take much more time and thorough research before AI replaces humans in medical centers.
Let us take a look at the potential of AI that it offers to the healthcare sector and its future in this aspect.

Types of AI of relevance to healthcare

AI is a collection of technologies that have direct relevance to the healthcare field and prove to be quite beneficial in the following ways-

Machine learning-

One of the most common forms of AI, Machine learning finds a place in most of the applications and systems in the healthcare industry.
Neural network is a complex form of machine learning used for numerous categorization applications. One such application is to predict whether a patient will develop certain symptoms or catch a particular disease. It solves problems in terms of variables or features associated with inputs and outputs.
Another complex form is deep learning, most commonly routed in oncology-oriented image analysis, radionics, detection of features in imaging data beyond perceived by the human eye.

Natural language processing-

AI is known for its various features such as speech recognition, translation application, text analysis and other language-related features. Thus, it is used to understand, create and classify published research and clinical documentation on patients. NLP systems aim to conduct conversational AI, transcribe patient interactions, preparing reports, etc.


Industrial robots can perform a variety of tasks such as delivering supplies, lifting furniture, repositioning beds etc. They not only assist the surgeons in the hospitals but also are used for creating precise incisions, stitch wounds and examine a particular area. Although vital decisions are made by humans only, the robots still find great use in hospitals.

Diagnosis and treatment applications-

AI has always focused on the diagnosis and treatment of diseases with the fastest method possible. Currently, rule-based systems are used widely. These are incorporated with EHR systems but lack precision and accuracy. If they were based on a more algorithmic approach, it would have been possible to handle them in a much easier and better way.
Many research labs and technology firms are working towards this, but not much results can be seen in clinical practice. Google has been collaborating with many startups to work on AI-derived image interpretation algorithms. Jvion recognizes patients who are at most risk of catching a disease and how effectively they would respond to treatment protocols. IBM h’s Watson provides a variety of services through APIs including vision, speech and language, and data-analysis programs based on machine learning.

Patient engagement and adherence applications-

To improve a patient's health, the engagement and adherence of the patient play a vital role. If a patient is told to make some behavioral changes such as filling prescriptions, losing weight or sticking to a treatment lab, then he needs to follow these. Noncompliance has always been a challenge for healthcare experts.
Thus, machine learning is being used to increase the involvement of the patient for a better health outcome. Emphasis on sending message alerts and appropriate content that can provoke actions is the need of the hour.
The software uses the patient data provided by smartphones, EHR systems, biosensors and conversational interfaces, compares it to all the effective treatment pathways possible and gives recommendations to patients as well as healthcare experts.

Administrative applications-

Healthcare organizations have been using chatbots for patient interaction, wellness and tracking the mental health of the patient. These NLP applications can be used for reminders, making appointments, filling prescriptions and other such purposes.
Relevant data is refined from a number of databases using machine learning, and the refined data is programmatically analyzed. This is done to find out correct and incorrect claims which save time and effort of healthcare experts and government.

Examples of AI in Healthcare-

Artificial intelligence has proved to be a boon to the healthcare industry. With less amount of time and reduced cost, doctors and hospital administrators are able to improve the lives of patients easily. Software, mobile apps, robots and systems are highly using this technology to add to the healthcare sector. Some of the examples include-

1. Enlitic

An AI company in San Francisco, Enlitic uses deep learning to develop medical tools for efficient diagnosis in radiology. Its platform analyses medical data such as blood tests, genomics, medical history of patients, radiology images, etc. and caters to the real-time needs of the patient.

2. Freenome

Freenome uses AI to detect cancer in the earliest stage possible and provide patients with the most effective treatments. The data obtained using AI in tests, blood reports and screening can also be used to develop new treatments for cancer.

3. Berg Health

BERG is a biotech platform that uses AI to speed up the discovery of exceptional medicines. A combination of traditional research and development and BERG’s Interrogative Biology is used to develop durable medicines that fight rare diseases. Recently BERG discovered unknown chemical links in the body that may be used for Parkinson’s Disease treatment.
Now that we have seen the importance of AI in the present world and how it has already been an advantage to many industries including healthcare, let us find out what future in AI holds for us.

The future of AI in Healthcare-

AI has already been used by numerous healthcare industries for speedy diagnosis and treatment of rare diseases, providing effective medicines, analyzing radiology images, speed and text recognition, refining of clinical notes and many other applications. It will be soon enough when most of the tasks will be done using Artificial Intelligence. The main challenge that AI faces is the adoption of these techniques in daily clinical practice. Public and healthcare experts are still suspicious about technology and need to be trained over time. AI will be a major part of the healthcare domain in the future and those who don’t adapt to these changes will not be able to cope up with the advancements in the world.

Other Blogs You Might Be Interested