Data Science in Healthcare: Benefits, Challenges & Applications
By: Vupputuri Chandana
Tags: Data Scientist, Healthcare, Data Science, Healthcare Technology, Machine Learning

According to the recent study, the data generated by the human are 2.5 quintillion bytes every day, which includes all the activities of the human and their health records. In order to handle this large volume of data, there is a need for technology. Over the ages, different technologies and methods are invented and are being used. One of the most important in such technologies is “Data Science”. Now a days, applications of data science are increasing in each sector like healthcare, education sector, banking and finance sector, IT sector, media and entertainment sector, e- commerce and many more.

One of the important sector which is in need of data science is healthcare. It helps to monitor the patient’s health by collecting data using different mobile application an helps the doctor to monitor the health condition from different locations, and also helps to detect the disease at an early stage.

Role of Data scientist in Healthcare Industry:

Data Scientist in healthcare plays an important role in implementing the data science techniques into healthcare and they also predict the disease at very early stage by extracting the useful data from the given information.

Major steps done by the data scientist are as follows:

Data scientist collects the data from the patients. Evaluating the hospital or health center requirement. Structure and sort information that can be utilized by the healthcare professionals. To carry out records analytics with the help of numerous tools. Implementing several algorithms to extract insights from the raw or unstructured facts. Constructing predictive models with the development groups.

Benefits of Data Science in Healthcare sector:

Now a days, Data science in healthcare is an essential element and factor that has transformed the industry. Many centers and processes had been advanced due to data science, technological know-how tools and techniques. It has boosted the speed of treatment and diagnosis. As a result, the workflow of the healthcare gadget gets superior. The real benefits of Data science in Healthcare are:

It helps in handling emergency condition adequately It reduce’s the waiting time for treating patients It offer’s on-time and proper treatment It smoothens the healthcare workflow It helps in reducing failure risk while treating any affected person

Challenges of Data Science in Health Care Sector:

Data Science in healthcare industry faces more challenges in areas such as data management, privacy & security and data retention:

Data Management: Health organizations face massive-information-related challenges which can affect patient safety. All facts that health companies gather wishes to be defined, formatted, deduped and checked for accuracy, and made available for various uses — clinical, billing, administrative — and the velocity and volume of the data makes this task harder. Some hospitals now employ patient safety experts, but in addition to having medical expertise, people in these roles must understand how data management practices can improve or hinder patient safety.

Privacy and Security: It is one of the most important challenges in the health care industry is being able to maintain the privacy desired and needed for the patient data and the security for preventing unauthorized access to the data base. Also, the importance to the privacy is being given less priority than it should be, considering the cost of the technologies to ensure safety and security of the data and networks. However, industry shall keep an extreme control and efforts to keep the data private and secure, to keep the trust of the patients and their data safe.

Data Retention: Health data must stay accessible for at least five years. That means businesses need to take a long-term approach for data maintenance and to keep track of information when the data gets accessed, by whom, and for what purpose. Medical data management software allows users to establish access privileges and processes, such as those that give temporary data viewing capabilities to representatives in different departments in a hospital. These products can index data and notes and track when data entered the system. Organizations must put processes in place to periodically sort through the data to delete it when appropriate, or modify and anonymize it to use it in new ways, such as to gauge trends across several years.

Applications of Data Science in Health Care Sector:

Drug Discovery and Manufacturing:

One of the important advantages of data science in healthcare lies in the drug discovery technique at an early-stage. This also includes the research & development, which includes subsequent-era sequencing and precision medicinal drug, that can even assist in finding opportunity paths for therapy of multi-factorial sicknesses. As of now, device studying benefits, techniques contains unsupervised studying, that may become aware of the patterns in facts without even imparting any predictions. Challenge Hanover, which is advanced with the aid of Microsoft, is the usage of the gadget learning-primarily based technology for multiple projects, which include the AI-based technology for cancer treatment and personalizing drug combination for the acute Myeloid Leukemia.

Medical Image Analysis:

Medicine and healthcare together form a promising field for utilizing technological advancements. The healthcare sector is acquiring new heights due to the advancements in Data Science. It is helping with various aspects, and one of them is the analysis of medical images. It is one of the most interesting areas of study in image recognition technology.

Data Science helps in the recognition of scanned images to figure out the defects in a human body for helping doctors make an effective treatment strategy. These medical image tests include X-ray, sonography, MRI (Magnetic Resonance Imaging), CT scans, and many more. Proper analysis of the images of these tests helps gain valuable insights for the doctors provide the patients with better treatment.

Helps in Identifying Disease and Diagnosis:

The primary advantages of data science in healthcare are to identify and diagnosis of disease and ailments, which are otherwise considered to be as hard to diagnose. This can include anything from the cancers which are tough to catch at the time of the initial stage to other genetic diseases. IBM Watson Genomics, which is even one of the above prime examples of how integrating cognitive computing with the genome-based tumor sequence, can help in making a fast diagnosis.

Virtual Assistance: By using predictive modeling techniques, data scientist has developed many virtual platforms that provide the assistance to the patients with more efficient, convenient and cost-effective. So, by using these platforms we can identify the disease of a person based on the confidence rate and the information they entered in the device.

One of the most popular examples of virtual assistants are “Ada AI chatbot” — It predicts the diseases based on the user’s symptoms, “Woebot” — a chatbot developed at Stanford University that provides therapy treatments to patients who suffer from depression, “MedWhat” — It is a virtual assistance uses machine learning to respond instantly to medical and health questions from both doctors and patients and many more.

Medications: From the Anesthesia to the treatment of breast cancer with daily drugs, the use of data science in healthcare are already being employed in the improvements of the medications. The famed IBM supercomputer Watson is also working with companies like the Pfizer to improve drug discovery, moreover, from the immunological conditions and cancer. Some of the companies like Medtronics are also working on to utilize machine learning to improve the medications, but, much more on the individual scale. Some of the channeling ideas about precision medicine, they are also working on with the patients to offer personalized feedback on how to better control and treat their diabetes. Personalized medicine will be a crucial strength of patients in the future.

Conclusion

Data science has been performing remarkably in the field of healthcare, from treating minor headaches to cancer. It is also helping scientists and doctors to be able to use the old data to understand the failures of the past and to provide improved and safe treatments for the future. There has been an increase in awareness about data science and the use of this in the sector. However, therein still a large scope of increase in the application of Data science in the field and acceptance of that from the users in health line sector, together to contribute to a healthy future.