DATA SCIENCE IN HEALTHCARE

 

USE OF DATA SCIENCE IN HEALTH CARE

Why do we use Data Science in Healthcare?

According to a study, the data generated by every human body is 2 terabytes per day. This data includes activities of brain, the stress level, heart rate, the sugar level, and many more. To handle such a large amount of data, now, we have more advanced technologies and one of them is Data Science. It helps monitor patients’ health using recorded data.

With the help of the application of Data Science in healthcare, it has now become possible to detect the symptoms of a disease at a very early stage. Also, with the advent of various innovative tools and technologies, doctors are able to monitor patients’ conditions from remote locations.

In earlier days, doctors and hospital managements were not able to handle multiple numbers of patients at the same time. And due to the lack of proper treatment, the patients’ conditions used to get worse.

 

However, now, the scenario has changed. With the help of Data Science and Machine Learning applications, doctors can be notified about the health conditions of the patients through wearable devices. Then, hospital management can send their junior doctors, assistants, or nurses to these patients’ homes.

Hospitals can further install various equipment and devices for the diagnosis of these patients. These devices built on top of Data Science are capable of collecting data from the patients such as their heart rate, blood pressure, body temperature, etc. Doctors get this real-time data of the patients’ health through updates and notification in mobile applications. They can then diagnose the conditions and assist the junior doctors or nurses to give specific treatments to the patients at home. This is how Data Science helps in caring for patients using technology.

Benefits of Data Science in Healthcare

Data Science helps in advancing healthcare facilities and processes. It helps boost productivity in diagnosis and treatment and enhance the workflow of healthcare systems. The ultimate goals of the healthcare system are as follows:

• To ease the workflow of the healthcare system
• To reduce the risk of treatment failure
• To provide proper treatment on time
• To avoid unnecessary emergency due to the non-availability of doctors
• To reduce the waiting time of patients

The Role of a Data Scientist in Healthcare

The role of a Data Scientist is to implement all techniques of Data Science for integrating it in healthcare software. The Data Scientist extracts useful insights from the data to make predictive models. Overall, the responsibilities of a Data Scientist in healthcare are as follows:

• Collecting data from patients
• Analyzing the needs of hospitals
• Structuring and sorting the data for use
• Performing Data Analytics using various tools
• Implementing algorithms on the data to extract insights
• Building predictive models with the development team

Now, let us discuss the major applications of Data Science in healthcare.

1)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 in 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 scan, and many more. Proper analysis of the images of these tests helps gain valuable insights for the doctors to provide the patients with better treatment.

 

 

2)Drug Discovery with Data Science

Drug Discovery is a highly complicated discipline. Pharmaceutical industries are heavily relying on data science to solve their problems and create better drugs for the people. Drug Discovery is a time-consuming process that also involves heavy financial expenditure and heavy testing.

Data Science and machine learning solutions are revolutionizing this process and providing extensive insights into optimizing and increasing the success rate of predictions.

Pharmaceutical companies use the insights from the patient information such as mutation profiles and patient metadata. This information helps the researchers to develop models and find statistical relationships between the attributes.

This way, companies can design drugs that address the key mutations in the genetic sequences. Also, deep learning algorithms can find the probability of the development of disease in the human system.

The data science algorithms can also help to simulate how the drugs will act in the human body that takes away the long laboratory experimentations.

With the advancements in the data-science facilitated drug discovery, it is now possible to improve the collection of historical data to assist in the drug development process. With a combination of genetics and drug-protein binding databases, it is possible to develop new innovations in this field.

Furthermore, using data science, researchers can analyze and test the chemical compounds against a combination of different cells, genetic mutations etc. Usage of machine learning algorithms, researchers can develop models that compute the prediction from the given variables.

 

3)Data Science in Genomics

Genomics is one of the interesting areas of study in medical science. It is the study for the sequencing and examination of genomes that consist of genes and DNAs of the living beings. The research on the genes of organisms facilitates high-level treatments. The aim of studying genomics is to find the characteristics and irregularities in DNAs. Also, it helps find the correlation between a disease, symptoms, and the health condition of the person affected. Further, the study of genomics includes the analysis of drug response for a particular type of DNA.

Earlier, before the emergence of powerful data analysis techniques, the study of genomics was a redundant and time-consuming task. This is due to the presence of millions of pairs of DNA cells in the human body. But, now, the applications of Data Science in healthcare and genomics has made this task easier. With the help of various Data Science and Big Data tools, we can analyze human genes with less effort and time. These tools facilitate researchers to find specific genetic issues and the drug that responds best for a specific type of gene.

Future of Data Science in Healthcare

Basically, there are four factors leading to rapid improvement in the healthcare industry:

• Technological advancements
• Digitalization
• Need for reducing treatment costs and duration
• Need for handling large population

Data Science has already started addressing all these to bring the desired effect. As Data Science is already doing wonders for society, there is no doubt that its application in the future will prove itself to be more invaluable. It will take the healthcare industry to further heights. Doctors will get ample assistance and patients will get a more personalized experience and perfect treatments.

CONCLUSION

In the end, we conclude that data science has many applications in healthcare. The medicine and healthcare industry has heavily utilized Data Science for the improving lifestyle of patients and predicting diseases at an early stage.