A Guide to Data Science in Healthcare: Applications

A Guide to Data Science in Healthcare: Applications | Data Science | Emeritus

Data is everything right now. Data science is growing rapidly and taking over every sector and industry in the world. The healthcare sector is not untouched by this changing reality. Data science applications in real life are also transforming medicine and everything we know about it. There are several concepts of data science that are being used in biotechnology and medicine.

There are a plethora of fields in the healthcare sector, such as drug discovery, medical imaging, predictive diagnosis, genetics, and several other data science applications in real life. Here are a few applications of Data Science in Healthcare.



1. Data Science for Medical Imaging

The first and foremost use of data science in the healthcare sector is medical imaging. There are several medical imaging techniques like CT scans, MRIs, and X-Ray. All of these medical imaging techniques help in visualizing the inner parts of the human body.
Earlier, doctors would manually check these image results and try to find irregularities in them. But, often, it was hard to look for microscopic deformities, and so the doctors were unable to suggest a proper diagnosis and treatment plan.
With the advent of data science, healthcare is facing growth. It is now possible to look for such microscopic deformities in these scans. Image segmentation has made it possible to look for the defects that are present in these scanned results.
Apart from this, data science healthcare has also given other image processing software like image recognition, image reconstruction, image enhancement, edge detection, etc. Many other methods are applied to improve and enhance these images and their outcome.

2. Data Science for Genomics

The study of sequencing and analysing genomes is called Genomics. A genome is made up of the DNA and all the genes of the organisms. The Human Genome Project, research has been advancing non-stop in this sector. So, it is now inculcated in the world of big data and data science. This has led to an increase in data science healthcare jobs.

Before computation was available, companies spent a lot of energy, money, and time on analysing gene sequences. This process was extremely tedious and expensive. But, with the advent of data science and its tools, it is now possible to analyse and create insights from the human gene at a much lower cost and in a much short time period. This helps create more data science healthcare jobs.

The research scientists’ goal in analysing genomic strands is to find defects and irregularities in them. Then, they look for the connection between the health of a person and genetics. Generally, researchers use data science healthcare companies. This is done to analyse the genome strands and try to look for a relation between the disease and the parameters contained within it.
Apart from the research that has already been done in bioinformatics and computational biology, there is a lot still left to discover.

3. Data Science in Drug Discovery

When it comes to drug discovery, it is a very complicated discipline. Pharmaceutical companies are greatly dependent on data science healthcare companies to find solutions for their problems. It is also so to make better drugs for the people. It is a time-consuming process that also involves heavy testing and financial expenditure.

Machine learning algorithms and data science healthcare applications are causing a revolution in this process. They are also giving extensive insights into the optimization and increase of the predictions’ success rates. Pharmaceutical industries make use of extensive insights from patient information. These are mainly patient metadata and mutation profiles, to help researchers develop models. It also helps look for statistical relations between certain attributes.

This is how companies can develop drugs that will focus on the key mutations in the genome sequences. This makes this one of the greatest data science healthcare applications.
With the advent of data science-facilitated drug development, the collection of historical data is also improved. It can help in the process of drug discovery. With drug-protein binding databases and genetics, new innovations have been made possible in this field. Researchers can also test and analyse the chemical compounds against different genetic mutations, cells and so on with data science healthcare management.

4. Predictive Data Analytics in Healthcare

When it comes to predictive analysis, healthcare is an important domain for it. It is the most common topic in health analytics. A predictive model makes use of historical data, looks for patterns, learns from them, and makes accurate predictions based on the patterns. It considers various parameters like finds and symptoms.
Data science healthcare management plays an important role in the improvement of patient care, management of chronic diseases, and increase in efficiency of pharmaceutical and supply chain logistics.

5. Monitoring Patient Health and Data Science

Data science healthcare management plays a huge role in the IoT devices that are available as wearable devices. These generally track temperature, heartbeat, and other medical parameters. Doctors can keep track of their patient’s blood pressure, calorie intake, and circadian cycle with the help of these tools. Other than these, these devices make use of real-time data. This helps find out if the patient will face any issues based on their present condition. As such, it assists doctors in making accurate decisions for their patients.

6. Tracking & Preventing Diseases with Data Science

Data analytics play an important role in the improvement of a patient’s health. It can help in notifying the doctor so that they can take some necessary steps to prevent any potential diseases. Powerful analytical predictive tools are used to find chronic diseases at an early stage.

7. Virtual Assistance with Data Science

With the assistance of disease prediction, data scientists have created an all-encompassing virtual assistance platform for patients. The patient can enter their symptoms in the input and receive insights about several possible diseases. Patients who suffer from psychological diseases can also leverage virtual assistants to obtain help for their daily activities.

The Bottom Line

These are the seven applications of data science in the healthcare sector that are improving this sector by leaps and bounds. By implementing these applications of data science, the healthcare sector is bound to excel to unmatched heights. Emeritus India through the data science programmes offered by leading global schools and universities to help you accelerate your career.

About the Author


Senior Content Contributor, Emeritus Blog
Varun, a seasoned content creator with over 8 years of diverse experience, excels in crafting engaging content for various geographies and categories. Leveraging this expertise, he seamlessly translates complex concepts into enriching educational content for the EdTech domain. His keen understanding of research and life experiences helps him resonate with students and create fact-based content. He finds solace and inspiration in music, nurturing his creativity for content creation.
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