The health market is the largest market in many countries that do not have many natural resources. Also, in countries like Iran, which has a lot of natural resources, the volume of the health market is still next to markets such as mining, oil and steel.

What matters in this market is the amount of data it generates, which Ponemon estimates is 30% of the world's health data.

For a long time, health, medicine, and treatment have been based on data collection and finding similar items in the data. The higher the rate of a case in the patients referred, the better our knowledge about that disease and how to manage and treat it. Since the advent of the Internet, the production of this data has become increasingly accessible. So that in many scientific articles and journals, websites of American and European government centers, genetic and pharmaceutical data can be easily used for free.

According to the words searched on the Internet, clinical trial information, electronic files, wearables, hospital management information, social networks and scientific articles, there is no shortage of data in the health industry.

But the main question that arises is what can be done with this large amount of data? How can data science help it?

Science or Data Science , interdisciplinary field that uses scientific methods, processes and mathematical algorithms, structured and unstructured data across tries, create new knowledge and vision. In the auto insurance industry, for example, data science can be used to determine which car factories are likely to produce safer cars, or which people in the community have safer driving characteristics.

What is the application of data science in the health industry?

The applications of knowledge extraction from health data are numerous; Here are some of them:

. Find new, personalized drugs and medicine

It will take about 12 years and $ 2.6 billion to find a new formulation and bring it to market. The pharmaceutical industry is one of the most expensive industries in the field of health and the main reason for its cost is the many tests and processes to produce better and newer drugs. If using the data, it is possible to work on the basis of the results of previous drugs and genomics data, both in the field of drug production or in the field of finding specific drugs for each person.

. Disease prevention and anticipation of new disease outbreaks

There are many articles on how diseases behave and how they occur. Both infectious and non-communicable diseases are no exception to this rule. Google data from 2003, 2008 and 2012 show that before the outbreaks of SARS , MERS and H1N1 outbreaks , large numbers of people in those areas searched for its symptoms. This suggests that if we had known the use of search terms at the time, we would probably have realized the prevalence of these diseases much sooner.

. Diagnosis of diseases

Another application of data science in health is to find the symptoms associated with each disease. Based on the data in scientific articles or the words used in search engines, the connection between different symptoms and diseases can be better found. Such physicians can diagnose diseases faster and better using Decision Support System or DSS systems .

. Treatment

To treat a person, the therapist must be able to determine the rate of complications, cost, and improvement of the person. This is why doctors who have seen more patients during their treatment are more successful in treating their new patients. If these conditions can exist using the available data for each therapist and can design and implement better programs according to their patient's condition. Meanwhile, according to the human genome project and the information contained in that project, it is even possible to personalize treatment plans based on the genetic information of each individual so that the treatment process is less complicated and more effective.

. Post-hospital care

Another post-hospitalization challenge is the care that patients must take for their condition. For example, after surgery, what are the risks or dangers that patients should be aware of? What should the doctor warn? In some cases, there is probably an emergency complication and the person should go to the hospital sooner? This is information that is currently available, but no specific results have been obtained due to the lack of data science.

These were just a few of the many uses for data science in healthcare. Given the amount of data that exists in this area and also the importance of this market for people, the use of data science will reduce the overall costs of this market and create a better quality of life for patients and people. Accurate data will be a great help in advancing the goals and path of telemedicine , and health startups will move in a better direction.