Implementing Artificial Intelligence In Healthcare

Despite the fact that most of us are afraid of AI, it is helping us in a variety of ways. Artificial Intelligence In Healthcare is revolutionizing the medical industry by providing a helping hand. This blog will help you understand the positive impact of Artificial Intelligence in the healthcare domain.

What Is Artificial Intelligence?

Artificial Intelligence is a process of using Machine Learning, Deep Learning, Natural language Processing, and many other techniques to build artificially intelligent models that can perform high-level computations and solve complex problems.

Artificial Intelligence in Healthcare

Since the introduction of Artificial Intelligence in the 1950s, it has been impacting various domains including marketing, finance, the gaming industry, and even the musical arts. However, the largest impact of Artificial Intelligence is in the field of healthcare. According to the latest report by PwC, AI will contribute an additional $15.7 trillion to the world economy by 2030 and the greatest impact will be in the field of healthcare.

In the below section you will understand how AI is being used to solve real-world use cases.

Artificial Intelligence in Data Management

Artificial Intelligence is benefiting healthcare organizations by implementing cognitive technology to unwind a huge amount of medical records and perform power diagnosis. Take, for example, Nuance the prediction service provider that uses Artificial Intelligence and Machine Learning to prescient the intent of users.

By implementing Nuance in an organization’s workflow one can develop a personalized user experience that enables a company to take better actions that enhance the customer’s experience and overall benefits business.

Here’s a list of key features of Nuance:

•Service acceleration: Suggest the best next step to ensure that the consumer’s needs are met.

•Call deflection: Minimize the volume of inbound call volumes and lower the expenses by anticipating the customers intent and diverting customers to other online engagements.

•Churn reduction: Using Machine Learning and Natural Language Processing techniques to predict the behavior of leads that may be close to invalidating their service based on their history, searches, sentiments, etc, and take appropriate action to avoid such service cancellations

•Automate tedious tasks: Eradicate the monotonous task of calling users by implementing an automated system that sends notification via SMS or email and uses AI-based chat bots that make things simpler.

Now let’s discuss how Artificial Intelligence is using Deep Learning techniques to improve medical diagnosis.

Artificial Intelligence in Medical Diagnosis

“Medical imaging and diagnosis powered by AI should witness more than 40% growth to surpass USD 2.5 billion by 2024.” – Global Market Insights. With the help of Neural Networks and Deep learning models, Artificial Intelligence is revolutionizing the image diagnosis field in medicine. It has taken over the complex analysis of MRI scans and made it a simpler process.

•MRI scans are difficult to analyze due to the amount of information they contain. A normal MRI analysis takes several hours and researchers trying to formulate an outcome from large data sets, wait for hours for a computer to generate the scans.

•Large and complex data sets can be analyzed with the help of neural networks and this is exactly what a team of researchers implemented in MIT. They developed a neural network called Voxel Morph that was trained on a data set of approx 7000 MRI scans.

•A neural network functions by inputting data at one end which undergoes transformation throughout the network until the final desired output is formed. Neural networks work on the principle of weights and bias.

Artificial Intelligence in Early Detection

Artificial Intelligence has played a key role in the early prediction of medical conditions such as heart attacks. Many AI-based wearable health trackers have been developed to monitor the health of a person and display warnings when the device collects something unusual or unlikely. Examples of such wearable’s include Fit bit, Apple watch, and many others.

‘Precaution is always better than cure’, this is the motto behind the latest release of the Apple watch.

•Apple used Artificial Intelligence to build a watch that monitors an individual’s health.

•This watch collects data such as a person’s heart rate, sleep cycle, breathing rate, activity level, blood pressure, etc. and keeps a record of these measures 24/7.

•This collected data is then processed and analyzed by using Machine Learning and Deep learning algorithms to build a model that predicts the risk of a heart attack.

Thanks to the Apple watch, an individual named Scott Killian saved his life.

Artificial Intelligence in Medical Assistance

As the need for medical assistance has grown, the development of AI-based virtual nurses has increased. According to a recent survey, Virtual nursing assistants corresponds to the maximum near-term value of USD 20 billion by 2027.

Sensely is one such example of a virtual nurse that implements Natural Language Processing, speech recognition, Machine Learning and wireless integration with medical devices such as blood pressure cuffs to provide medical assistance to patients.

Here’s a list of key features that the virtual nurse, Sensely provides:

•Self-care

•Clinical advice

•Scheduling an appointment

•Nurse Line

•ER Direction

With such revolutions in the field of healthcare, it is clear that despite the risks and the so-called ‘threats’, Artificial Intelligence is benefiting us in many ways.

Artificial Intelligence in Decision Making

Artificial Intelligence has played a major role in decision making. Not only in the healthcare industry but AI has also improved businesses by studying customer needs and evaluating any potential risks.

A powerful use case of Artificial Intelligence in decision making is the use of surgical robots that can minimize errors and variations and eventually help in increasing the efficiency of surgeons. One such surgical robot is the Da Vinci, quite aptly named, allows professional surgeons to implement complex surgeries with better flexibility and control than conventional approaches.

Key features of the Da Vinci include:

•Aiding surgeons with an advanced set of instruments

•Translating the surgeon’s hand movements at the console in real time

•Producing clear and magnified, 3D high-definition image of the surgical area

Surgical robots not only assist in decision-making processes, but they also improve the overall performance by increasing accuracy and efficiency.

So those were a couple of real-world applications of Artificial Intelligence in healthcare. Throughout the blog, I’ve mentioned two very important fields of AI, Machine Learning and Deep Learning. Let’s understand what exactly these terms mean.

‍