Healthcare sector has been pioneer in adapting technology for increasing their overall efficiency. The novel Machine Learning algorithms developed by scientists have also been used lately by healthcare to achieve shocking results in disease diagnosis accuracy, manufacturing of new drugs and vaccinations, Predicting outbreak of epidemics, and the development of new smart healthcare gadgets. It is a known fact that the larger the data better is the accuracy of Machine learning algorithms. The availability of huge medical datasets containing Diagnosis reports of thousands of patients, Drug study and research reports of the past couple of decades, collection of study of Patient behavior, etc is aiding the machine Learning algorithms big way. Newly designed mobile apps and biomedical sensors are also generating huge amounts of data which is enabling better training of Supervised and unsupervised Machine Learning Algorithms.
Few Doctors have warned about the extreme side effects of over usage of Machine Learning in the healthcare domain. There are also few instances where Machine learning scientists claimed to achieve big in the medical field but the results proved that these models underperformed as compared to human experts as in IBM Watson’s case. But scientists are considering these warnings and failures as mere hurdles that need to be overlooked.
To quote an example, Professors of IIT Roorkee have shown in their research paper in 2019 https://ieeexplore.ieee.org/document/8943993 that Machine Learning algorithms namely Support Vector Machines (SVM) and Random Forest can achieve up to 93% accuracy in predicting the presence of Heart Disease in a patient. It takes a couple of minutes for the machine to generate the diagnosis results substantiating its effectiveness in classifying a patient as diseased or healthy. For a Doctor, it would be very difficult to achieve such accuracy and that too in a couple of minutes.
This is just an example to demonstrate the effectiveness of Machine Learning Algorithms in assisting Healthcare Professionals. There are a plethora of other research works being carried by Machine Learning scientists worldwide to build effective models for early detection of diseases like Tuberculosis, Alzheimer’s, Cancer of all types, etc.
Other than Disease Diagnostics, Machine Learning is being deployed in some other amusing areas of healthcare. To quote a few:
• Machine learning algorithms works wonderfully in reducing the number of hours required for preclinical research and clinical trials of drug discovery. Drug discovery is a time-consuming process and generates a lot of biological data. The very nature of Machine Learning algorithms to detect specific patterns in this data helps to speed up the process of Drug Discovery. The report “Global Artificial Intelligence in Drug Discovery Market Size Analysis, 2018-2028” Bekryl Market Analysts indicates that Machine Learning offers a saving of USD 70 billion to the Drug market.
• Machine Learning helps in speeding up the process of Vaccine Design because of its ability to detect specific patterns in Genomic data. There are lot of research papers published in last six months which demonstrate how Machine learning can be used to find COVID vaccine in shorter period of time. As a result, many Drug Manufacturers have claimed to complete the design of the COVID vaccine by early 2021 which would have otherwise taken an extra year.
• Predicting outbreak of a Pandemic/Epidemic is another potential application of Machine Learning Algorithms. The accurate outbreak pattern of COVID Virus in different parts of the world can be quoted as a proof. It was predicted that in the USA almost 2.5 lakhs citizens will surrender to COVID in 2020 which is becoming a reality now. It was accurately predicted that the Indian Subcontinent will see a widespread COVID infection during monsoon in AUG-Sep, 2020, which also became a reality.
• Intelligent Patient interrogation platforms are being developed using Machine Learning algorithms which act like a Chabot and interact with the Patient to help find the suitable medical treatment for him/her.
• Lot of work is being done to develop Machine Learning Algorithms that can analyze doctor’s performance and help a patient to find a suitable Doctor for his treatment.
Apart from the big players there are multiple Startups that are doing a wonderful job in applying the Machine Learning model in various medical processes. To name a few: MD Insider, Quotient Health, KENSCI, CIOX Health, PATHAI, Quantitative Insights, INSITRO, BIOSYMETRICS, CONCERTO Health AI, ORDERLY Health, BETA Bionics, Prognos..
To find more about the initiative of these companies please visit their websites
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