Applications of Machine Learning in Healthcare

Applications of Machine Learning in Healthcare

Machine Learning is the science of programming machines such that they can learn automatically from data, identify patterns and make decisions.

 Machine learning is used in various fields to provide accurate and timely solutions. It is predicted to completely transform all fields in the near future. This technology also holds a better chance of growth in the future for tech aspirants. To fast forward your career there are various AI ML Courses available.

 Medicine and healthcare is one such field. As the population and healthcare needs are increasing, Artificial Intelligence and Machine Learning are being used to meet the growing healthcare demand. Machine learning can provide more efficient, precise, and improved healthcare to larger numbers at less cost.

Some examples of the applications of machine learning are-

1. Managing patient data

Machine learning is being used to streamline patient recordkeeping. An example includes Natural Language Processing which is used to record patient data, thus reducing manual effort. Electronic Health Records(EHR) are maintained more efficiently.

2. Disease Diagnosis

Machine learning is being used to detect diseases by analyzing X-ray images, patient data, etc. They can be used to provide a more accurate and timely prediction of diseases. It has been used in covid -19 detection. A deep learning-based model developed by MIT can even detect breast cancer development years in advance.

3. Robotic Surgery

Robots created by AI are also being used to perform complex surgeries where precision is required, and there is none-scope for human error. Machine learning is used to improve the performance of robotic surgeries.

4. Providing patient care and support

 Machine learning is used to provide more personalized and continuous 24×7 Care to patients. Robots are even being used to provide walking support to patients with paralysis, provide companionship to older patients, etc. Machine learning is being used for medication reminders to patients as well. Many times, the patient may not be able to consult a doctor or may need real-time advice. Machine learning-based technologies Bot systems can come in handy in such situations.

5. Drug development and research

 Machine learning is being used to develop medicines. This also includes next-generation sequencing and precision medicine. AIML is being used for research in fields like cancer treatment.

6. Personalized treatment

Machine Learning can also be used to develop more personalized medical care and prescription of medicines based on patient history and data. A physician cannot continuously monitor all patients or study each patient’s history and genetic information. This is one of the areas where ML can be used to study data in thousands or even millions and provide personalized medicines and other treatments.

7. Clinical Trials and Research

Machine learning is being used to speed up and aid clinical trials and research. For example, medical research requires suitable candidates. Machine learning(ML) helps analyze data and screen potential candidates, thus saving time and cost. It is also used to monitor the candidates. ML aids research by analyzing vast data and saving on manual efforts.

8. Predicting outbreaks

Machine learning is being used to predict disease outbreaks. They analyze data of the population of a region and other factors. As the ML models can analyze very large volumes of data, they can be used to predict outbreaks. Recently, in covid-19, ML models have been used to predict outbreaks or spikes in the disease.

9. Radiology

Machine learning is being used in the field of radiology. Neural networks are being used to detect, recognize and analyze cancerous lesions from images. Due to faster processing speeds and cloud infrastructure, ML applications can detect anomalies beyond what the human eye can see.

10. Predicting diseases in advance

By predicting diseases in people in advance, they can be prevented. This can be data based on a patient’s medical history, genetic information, lifestyle, diet, and other such factors. Classification machine learning algorithms like KNN, Decision Tree, and Naive Bayes are being used to predict diabetes. Classification and clustering algorithms are used to predict liver diseases.

11. Aiding lifestyle changes

Many applications of machine learning are being used to give personalized advice to people, such as fitness routines, diet charts, medicine reminders, etc., to prevent diseases they may be prone to. These applications can provide 24X7 personalized assistance to people, which is not possible through traditional healthcare practices.

 12. Crowdsourcing medical data

 Many people these days are sharing their medical information. This allows researchers and doctors to access large volumes of data which will aid in further research. The data is shared with the person’s consent. For example, Apple’s Research Kit provides users with apps implementing machine learning-based facial recognition models to treat Asperser’s and Parkinson’s disease.

13. Preventive Healthcare

 Researchers are also using ML-based applications to study the causes of diseases. The genetic information of patients and other factors causing diseases are being studied. With the help of ML, the causes of diseases can be studied as ML applications can process very large information in very little time and help detect patterns and make predictions.

 In many cases, like cancer detection, machine learning-based applications are increasingly performing better than humans. There are various machine learning applications in the field of nutrition and fitness as well, which will further aid the health of the people. There are numerous other applications of machine learning in healthcare, such as in the insurance sector, medical personnel management, etc.

John Norwood
John Norwood is best known as a technology journalist, currently at Ziddu where he focuses on tech startups, companies, and products.