The 21st century is often referred to as the age of data and this couldn’t be any more true in today’s scenario. Data is now indispensable in our everyday lives. Owing to this massive growth in the importance of data, a field of study has emerged that has taken the world by storm – data science. The applications of data science are innumerable and data scientists are now needed in every industry present around the world. Healthcare has benefited greatly from the evolution and advent of data science. This article takes a look into various applications of data science in healthcare.
Major Applications of Data Science in Healthcare
The most visible application of data science in healthcare can be witnessed in the field of medical imaging. With developments in X-Ray, MRIs, CT Scans and more, doctors can peer into the workings of the human body better than ever before. In the past, doctors had to manually inspect these images and find irregularities within them. However, finding microscopic irregularities often ended up being a challenge, hindering them from giving an accurate medical diagnosis.
With the growth of deep learning technologies in data science, doctors were able to overcome this hurdle and accurately pinpoint even the tiniest of irregularities in these scans. Through image segmentation, it is possible to search for defects present in the scanned images. More and more research is being done on this to get better accuracy when it comes to the detection of anomalies.
Drug discovery, being a highly complex and critical field of study, has benefited greatly from the adoption of data science. Pharmaceutical industries are now relying on data analytics to collect data, decipher patterns, solve problems and create better drugs to cure more diseases. Drug discovery is an extensive time and capital consuming process. Machine learning algorithms, artificial intelligence, and automated data analytics processes can help reduce the time and money needed for drug discovery.
Data Science can also forecast how any drug will act in the body using advanced and automated ML and AI algorithms and simulations. This greatly helps shorten the time needed for a drug to hit the public market. With the advent of data-science fueled drug discovery, we are now capable of accurately collecting historical data which helps assist in the drug development process. With an amalgamation of genetics and drug-protein binding databases, it is possible to develop innovations in this field.
Another major application of data science in healthcare can be seen in the field of genomic medicine. Data science has helped genomics by enabling an advanced level of research and the delivery of treatment personalization plans for patients. Data science and its subsequent fields of study have helped researchers understand the impacts of DNA on our health and figure out biological connections between genetic diseases and drug effects.
Genomics uses the Map Reduce programming model, a data science technique to enable doctors to effectively read genetic sequence mapping. Genomics research also involves getting a deeper insight into the way a drug reacts to a particular genetic issue. Data science tools can help reduce the time taken for this study.
Applications of data science in healthcare are not just bound to these three aspects. Data science has properly integrated itself into the world of healthcare and helped millions of people worldwide. The need for data scientists has also subsequently increased. Praxis, a premier business school, identifying this rising need, has developed a state of the art PGP in Data Science for aspiring data scientists. This tailor-made program will ensure that you have all the tools necessary to make your mark as a proficient data scientist. Visit our website to learn more.