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7 Applications of Machine Learning in Healthcare Industry

Last Updated : 03 Oct, 2021
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The Healthcare industry is an essential industry that offers care to millions of citizens, while at the same time, contributing to the local economy. Artificial Intelligence is benefiting the healthcare industry in numerous ways. Information technology is revolutionizing the healthcare industry by providing a helping hand. As we know, AI is the development of computing systems that are capable of performing tasks that typically require human intelligence. These involve heavy tasks like decision making, solving complex problems, object detection, and much more. The benefits of technologies, such as, increased level of accuracy and high level of computation, which take days for humans to solve manually are getting implemented into the healthcare business to enhance the services and keep the data organized.


Machine learning is an application of AI which has impacted various domains including marketing, finance, the gaming industry, and even the musical arts. However, the largest impact of Artificial intelligence is on the field of the healthcare industry. According to a report of PwC, AI will contribute an additional $15.7 trillion to the world economy by 2030, while the greatest impact is to be estimated on the healthcare industry.

Causes for Sudden Growth of AI in Healthcare

Let us narrow down the reason behind the sudden growth and application of Machine Learning in the healthcare industry. There are two major points that have made AI so impactful in the field of healthcare.

  • High availability of medical data – With the availability of data, implementing artificial intelligence gets much easier. AI is based on technologies such as deep learning and machine learning which requires tons and tons of data. So it becomes easier for the healthcare industry to track the record of their firm by a properly organized data setup.
  • Development of complex algorithms – The introduction of complex algorithms led to the development of machine learning in the healthcare industry. Particularly the medical data is of very high dimensional in character, the data is very vast, it has thousands and thousands of attributes, machine learning played a major role in the healthcare industry through the complex problem-solving feature.

Applications of Machine Learning in the Healthcare Sector

The growing number of applications of machine learning in healthcare allows the health care industries to manage their data and enhance their services effectively. Let’s look at a couple of applications of machine learning in the healthcare industry.  

1. Managing Medical Data

Machine learning is actually advancing the health care industry by implementing cognitive technology in order to unwind a huge amount of medical records and also in order to perform any power diagnosis. Machine learning helps predict the intent of a user. Implementing machine learning in an organization’s workflow can develop a personalized user experience that allows the company to make better decisions and better actions that enhance the customer’s experience which benefits the organization. Therefore, machine learning helps to store, collect and reform data.

2. Helps in Medical Diagnosis

According to the Global Market Insights, Medical imaging and diagnosis powered by AI should witness more than 40% growth to surpass $2.5 billion by 2024. With the help of machine learning and deep learning models, AI is actually revolutionizing the image diagnosis field in medicine. The one major application of AI in medical diagnosis is MRI scans. AI has taken over the complex analysis of MRI scans and it has made it a much simpler process.

3. Detecting Diseases at an Earlier Stage

Machine learning played a very important role in the early predictions of medical conditions such as heart attacks and diabetes. There are many AI-based wearables that are being developed to monitor the health of a person and display any warnings when the devices observe something unusual or unlikely. For eg:- Fitbit and Apple watch. These devices monitor a person’s heart rate, sleep cycle, breathing rate, activity level, blood pressure, so on. It keeps the record of these measures 24×7.  

4. Machine Learning in Medical Assistance

As an engine for medical assistants has grown the development of artificial intelligence-based virtual nurses has increased according to a recent survey, virtual Nursing Assistants corresponds to a maximum of 20 billion u.s dollars by 2027. A virtual nurse helps to monitor patients’ conditions and follow up with treatment between the doctor visits.

5. Machine Learning in Decision Making

AI has played a very important role in decision-making not only in the field of health care, but AI has also improved businesses by studying customer needs and evaluating any potential risk that a business might face. A powerful use case of artificial intelligence in decision-making is the use of surgical robots that can minimize errors and any variations and will eventually help in increasing the efficiency of your surgeons. They help implement complex surgeries with better flexibility and control than any other approach.  

6. Personalized Medicine

The predictive analysis of Machine learning can help users to get personalized treatment. Generally, nurses are bound to choose from a specific set of diagnoses or predict the risk to the patient using a fixed formula based on the history and available genetic information. Whereas, machine learning in medicine predicts the data of the patient by analyzing the medical history to generate multiple treatment options. Due to these treatments being based on the user’s data they’re more likely to suit the patient and are more personalized.  

7. Helps Analyze the Errors in Prescriptions

Machine learning can detect and analyze the errors in the prescriptions too. The intelligence can inspect the patient’s health records with the given prescriptions to find and correct the possible errors in the medication.

Conclusion: In health care industries, the intelligence by various data science models, without any human intelligence, can provide accurate and efficient results with little to no time. The machine learning models help health care sectors in numerous ways, by establishing accurate and efficient suggestions or by reducing the manual tasks of healthcare professionals, hence allowing them to focus on the research area and enhance their performance in urgent cases.

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