Impact of Data Science in Healthcare

Data Science is becoming an important technology, revolutionizing many sectors. Industries such as IT; education; banking and finance; media and entertainment; e-commerce; and healthcare are capitalizing on it. Here, at hassis.AI, our team is trying our best to be an important and supportive part of the healthcare sector, hence, this article will focus on various applications of Data Science in healthcare, in order to provide useful information on how Data Science can be an effective ally of the sector.

Data Science is, in fact, a game-changing and essential to healthcare. To understand this, we have to look at various problems and facts that are associated with healthcare, and how Data Science deals with them. First and foremost, the data generated by every human body is a staggering 2 terabytes per day. Data such as stress level; heart rate; sugar level; activities of the brain and many more, will be extremely hard and tedious to track without the help of Data Science. Through these tracking of the patients’ data, doctors can monitor many patients at the same time, on site or even remotely through innovative tools and technologies build upon Data Science. Secondly, it is crucial for hospitals and healthcare institutions/facilities to apply Data Science, because it helps smoothing the operation and management, unlike the early days when it was extremely challenging for doctors to handle large number of patients at the same time. Data Science allows healthcare systems to punctually provide proper treatments and reduce the risk of treatment failure for patients.

Behind the implementation of Data Science are Data Scientists, as they are responsible for integrating the technology into healthcare software. They will collect the data from patients, structuring and sorting the data, then store it for usage. They can use the data to analyse the needs of hospitals; perform data analytics; implement algorithms to extract useful insights and build predictive models. Through techniques used by the Data Scientists, many major applications were built, which we will discuss now.

One of the major applications in healthcare is medical image analysis. Using Data Science, doctors can create an effective treatment strategy through the recognition of scanned images such as X-ray; CT scan; sonography; Magnetic Resonance Imaging; etc. By properly analyzing these image tests, doctors can figure out the defects in patients’ bodies, in order to provide valuable insights and give better treatments. Currently, there are three common algorithms used in medical image analysis. The first one is Anomaly Detection Algorithm, and it helps identifying, for example, bone fracture and displacements. The next one is Image Processing Algorithm, and it supports in analyzing; enhancing and denoising images. The last one is Descriptive Image Recognition Algorithm, which visualizes and extracts data from images, interprets it and makes use of it to form a bigger picture (e.g merging the images of the brain scan and designating them accordingly). These algorithms can be successfully implemented by using supervised and unsupervised algorithms.

Another major application of Data Science in healthcare would be in predictive analytics. By efficiently collecting information or data about the patient, healthcare systems can then use them to analyse and identify symptoms; stages of the disease; level of damage to the body; etc. From then on, a predictive analytics model built on top of Data Science can make predictions on the condition of the patient, and help doctors to give appropriate treatments on time.

Drug research is also revolutionized by Data Science. It has always been problematic for medical research institutions to create medicines or vaccines for new diseases in short time. This is due to the fact that to find a formula for a medicine, researchers have to thoroughly understand the characteristics of the causative agent, and it may require millions of test cases to figure out. After that, many further tests and trials must be performed to make sure the formula is good for consumption. To go through this process, in the past when Data Science wasn’t developed, it required 10 to 12 years. Now, with the help of Data Science, drug research has become a much easier and faster task. Data from millions of test cases can be processed within way shorter time, weeks or months maybe. This leads to vaccine and medicine being tested; guaranteed and launched in less than a year.

Genomics – the study of the sequencing and examination of genomes that consist of DNAs and genes from living beings, is supported tremendously using Data Science. The main goal of the field is to find the characteristics and irregularities in DNAs. It also helps finding the correlation between disease; health condition and symptoms of the patient. Furthermore, genomics studies can analyse drug response for a particular DNA. Before the help of Data Science, the study of this field was time-consuming and redundant. Nowadays, just like drug research, Data Science improved the process a lot better. Analysis of human genes requires less time and effort, using Data Science and Big Data tools.

Healthcare applications are being built with integration of Data Science, in order to provide virtual assistance for patients. Through comprehensive platforms that can offer personalized experiences, patients are supported tremendously. All it takes is to simply type in the symptoms, and the application will identify or predict the disease and the condition of the patient. It will then suggest medication, precautions, and the treatment required. In short, these virtual assisting applications can guide patients through every stage of the disease, and help them recover.

To sum up, Data Science is doing wonders for the healthcare sector. It supports technological advancements and digitalization of healthcare. It also helps reducing treatment costs and duration, while facilitates handling an increasingly large population.?