The traditional way of performing tasks is becoming obsolete now. Smart machines have changed the overall observation of the Healthcare sector. Doctors are using artificial intelligence for diagnosing diseases in patients. Machine learning is performing a great job in the Healthcare sector. We will discuss here what machines are doing in hospitals as well as the benefits of machine learning in the healthcare sector.

What is Machine Learning?

Machine learning is the branch of Artificial Intelligence that makes predictions by using computers. It is the study of algorithms and it gives an ability to computers to work automatically.

Benefits of Machine Learning in the Healthcare Sector

  • Drug discovery and medicine prescription
  • Diagnosis of Heart disease
  • Smart electronic health recorder
  • Prediction of Polycystic Ovarian Disease
  • Prediction of diabetes
  • Surgery using robots
  • Personalized treatment
  • Cancer detection
  • Radiotherapy
  • Support Medical research
  1. Drug discovery and medicine prescription

Machine Learning helps in discovering and designing drugs. It makes the process of making drugs faster. Moreover, it helps in reducing the extra cost of drug delivery in the market. Today’s several companies are working on the principle of making drugs on their own. BenevolentAI also using Artificial Intelligence in the drug discovery process.

  1. Diagnosis of Heart disease.

Heart disease can of any type like coronary heart disease and coronary artery disease. Researchers use SVM and Naïve Bayes algorithm. The WEKA data mining tool can be used for data analysis. Anomaly detection algorithms used for predicting heart attacks.

  1. Smart Electronic health recorder

These days maintenance of up-to-date health records is quite a tricky process. The major role of ML in the healthcare sector is to makes the process easy and efficient. Optical character recognition helps to develop a smart electronic health recorder. It helps in solving patient queries either through mail or automated call. The main motive is here to give fast accessible systems.

  1. Prediction of Polycystic Ovarian disease

Different machine learning algorithms are effectively used for predicting polycystic ovaries in females. Machine learning use clustering and classification algorithm for predicting polycystic ovarian disease. It will provide ease to the doctors in knowing whether the female is suffering from a single cyst or of polycystic.

  1. Prediction of diabetes

Diabetes is a serious problem that can impact human health. It can damage various body parts like heart, nerves, and kidney. Different classification algorithms like the random forest, KNN,  decision tree predict diabetes in less amount of time.

  1. Surgery by using robots

Robotic surgery is one of the standard machine learning applications in healthcare. This application can be divided into various subcategories such as surgical skill evaluation, improvement of robotic surgical materials, automatic suturing and surgical workflow modeling. Suturing is the procedure of stitching up an open wound. Computerization of suturing may decrease the surgical procedure length. Researchers are trying to relate a machine learning method to assess surgeon presentation in robot-aided slightly invasive surgery.

  1. Personalized treatment

Machine learning also provides personalized. The objective of this area is to deliver better service based on individual health data. It makes use of predictive analysis. Computational and statistical tools help in knowing the patient’s symptoms and generate their genetic information. One of the examples is SkinVision in which a person can detect online whether he is suffering from skin disease or not.

  1. Cancer detection

Machine learning approaches help in detecting and classifying tumors. Deep learning is very helpful in predicting the same disease. Chinese researchers discovered a cancer type classifier known as DeepGene. Convolutional neural networks are also helping in detecting tumors and also it gives accurate results.

  1. Radiotherapy

Researchers are putting all efforts in collaborating AI and Machine learning in radiology. In radiology, machine learning uses classification algorithms to classify the disease according to the category. Researchers use Google’s DeepMind Health to develop algorithms that help in detecting healthy and cancerous tissue.

  1. Support Medical research

Scientists and researchers are regularly working on research and collecting more and more data. Natural language processing, deep learning, and neural networks provide valuable research insights to the researchers. Thus knowing Machine learning also supports efficient medical research.

Also read: Artificial Intelligence Vs Machine Learning Vs Data Science

Machine learning since the last decade has given so many advancements to society. It has numerous benefits in different fields. From nanobots to drug discovery it has given a lot to society. In this blog, we have learned about machine learning in the healthcare sector.


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