Big Data and Data Science are revolutionizing diverse sectors across industries. From the energy sector to defense, from government agencies to finance, Data Science, with its sidekicks, including machine learning and artificial intelligence, are replacing conventional processes and laying out new avenues for transforming day-to-day human lives. And the healthcare industry is no exception. Healthcare is undergoing a drastic transformation, thanks to technology.

The healthcare industry is rapidly evolving, leveraging technology to offer improved patient care and efficient diagnosis. Data Science has revolutionized several pivotal elements of healthcare, and this seems only like it is taking off.

As we gear up for the next decade, Data Science sure has some interesting use-cases and applications that are completely metamorphosing healthcare.

Here’s a list of various use cases and applications of Data Science in healthcare:

Medical Image Analysis

Medical imaging immensely helps in diagnosing life-threatening conditions, including tumors, artery stenosis, or organ delineation. Magnetic resonance imaging (MRI), X-ray, computed tomography, and mammography are the popular medical imaging techniques to obtain clear, higher resolution, denoised images that can help in offering a more accurate interpretation of the patient’s condition. Data science technologies and machine learning methods help collect an enormous amount of data that is stored with the help of digital storage systems. This data is then used effectively to detect diverse conditions, offer better treatment options, and also aid in predictive care.

Genetics and Genomics

Personalization and bespoke services are the popular trends of the 21st century, and healthcare, of all the industries, should not be an exception. Genetics and genomics open up the path to personalized medical care. Data science facilitates the virtue of DNA study, biological connections between genetics and health, in turn helping with personalized treatments.

Data Science tools also help in genetic sequence mapping, shortening the time for efficient data processing, retrieving genomic data, and DNA sequencing.

Also read: Five technologies that can give your hospital a competitive edge

Virtual Assistance for Patients and Customer Support

Remote healthcare and virtual assistance for patients or in geographical locations that require remote assistance (for example, epidemic-stuck areas), Data Science is the future. AI-powered mobile apps can connect the patient to the healthcare and chatbots that help in offering basic healthcare support. These chatbots can also gather symptoms and receive vital information for the patients remotely before the doctors can offer full-fledged medical care. This not only helps in providing instant care but also saves patient time in waiting rooms, prioritizing critical patients over less urgent patients. With automation powered by Data Science, healthcare organizations can offer improved customer support.

Predictive Medicine and Improved Diagnosis

Missed or incorrect diagnosis is still one of the grave problems faced by the healthcare industry. According to research, around 5% of the adult patients in the United States are misdiagnosed, and the number is higher when researched in post-mortem reporting. Data science can help in curtailing this number by improving the accuracy of diagnosis and offering improved predictive medicine with the help of using and applying historical data, medical imaging, sound recognition technologies, and deep learning algorithms to create accurate predictions.

Further, it also helps in avoiding the risks involved in offering prescription medicines by studying the databases and cross-verifying it against the offered standard treatment.

Data science pioneers an improved way of maintaining E-health records, which helps in garnering heightened customer engagement. Patients can actively participate in the care offered to them, and healthcare givers can improve care coordination.

Read more: The connection between digital health and patient satisfaction

Creation of Pharma Drugs

Pharma drug production is one of the most vital elements of improving healthcare and extending future-proof healthcare for mankind. One of the biggest challenges in discovering and producing drugs is testing the effects of a drug, implementing a series of test cases, and then proving its viability before it gets approved and hits the market. Data science helps to fasten this process with the help of algorithmic procedures, machine learning, simulation, and modeling. Data science facilitates computation drug discovery by collecting data, applying it in the drug development process, and building models instead of carrying out actual lab experiments.

To Summarize…

Data science is here to reshape the healthcare industry – from hospital management, patient care, to drug production. Integrating Data Science can open up new and improved ways of offering healthcare, minimizing errors in medical diagnosis, and extending a holistic approach towards healthcare.


Are you ready for the smart hospitals of the future, powered by data science?