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Data Science

Applications of data science in healthcare

Industries are rapidly adopting data science to thrive in today’s data-driven world. The healthcare industry is one of those industries that is tapping into the potential of data science to diagnose diseases accurately and prescribe appropriate medication.  

The applications of data science in the healthcare industry range from predicting future disease outbreaks to providing market intelligence to help pharma companies promote drugs effectively.  

This article briefly describes about some of the primary uses of data science in the opportunity-rich healthcare industry. 

Medical Imaging 

Various imaging techniques such as X-ray, CT Scan, MRI, etc, play a major role in disease diagnosis. However, identifying microscopic deformities is beyond the capabilities of even a well-experienced physician. Data science and deep learning technologies make it possible to identify minute deformities in scanned images through image segmentation. Other image processing techniques such as image enhancement, image recognition, image reconstruction, edge detection, etc, also help in improving the accuracy of diagnosis.   


The study of analysis and sequencing of genomes is known as Genomics. A genome encompasses the DNA and all other genes of an organism. Before the advent of powerful computation, companies had to spend huge amounts to analyze the sequence of genes. Besides being expensive, the process is also tedious. However, with the help of advanced data science tools, bio firms are now able to analyze human genes and extract insights faster and in an economical manner. 

With data science, research scientists can analyze genomic strands to identify irregularities, connections between genetics, identify the right drug and its reaction to a particular genetic issue, etc. The discipline that combines genetics and data science is known as Bioinformatics. 

Drug discovery 

It’s a wide-known fact that drug discovery is a time and money-consuming process as researchers have to work on thousands of information to formulate an appropriate drug for a disease. However, the emergence of data science, machine learning, and deep learning is changing the drug discovery process and providing in-depth insights to create the right drugs. Even more, data-science enables researchers to study and test chemical compounds against different cell combinations and genetic mutations. Also, researchers can build models that predict the drug effect of the given variables.  

Predictive analytics 

One of the most popular topics, predictive analytics is predominantly used in the healthcare industry to identify patterns, correlations, etc, from historical data to make meaningful predictions. In recent times predictive analytics is playing a major role in improving chronic disease management, population health management, patient care, pharmaceutical logistics, etc.  

Disease prevention 

Data science plays a significant role in preventing potential diseases by enabling medical practitioners to constantly monitor a patient’s health and detect chronic illness in its nascent stage. Many times, not recognizing disease at an early stage due to negligibility has led to extreme cases. This has been highly detrimental to the patient’s health as well as economic costs. The advent of AI and data science is greatly helping the healthcare industry to change this situation. In fact, many AI platforms have been built to detect diseases at an early stage. For example, in Brazil, a group of researchers from the University of Campinas has built an AI platform to diagnose the Zika virus. 

Summing Up 

Data Science is not only improving the lifestyle of patients but also medical practitioners. To conclude, with data science the medical industry can soon find a cure for deadly diseases like cancer and prevent future epidemics or pandemics. 


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