With machine learning and artificial intelligence applications, it may be possible to prevent diseases and learn future disease risks in advance from the HBYS data accumulated for many years.

1. CAN ARTIFICIAL INTELLIGENCE
PREDICT DISEASES WITH HBYS?
Tuğçe ARSLAN

2. With Machine Learning (ML) and Artificial Intelligence (AI) applications,
it may be possible to prevent diseases and learn future disease risks in
advance from the HBYS data accumulated for many years.
Turkey has been one of the rare countries that regularly uses HIMS in all its hospitals for
many years. Due to the long–term use of HBYS, there is a large amount of patient data. With
the help of HBYS, more and more detailed data are collected day by day. When these data
are evaluated with Artificial Intelligence (AI) and Machine Learning (ML) technologies, it will be
an excellent opportunity to detect disease risk in the future.
HBYS data consists of vital data related to diseases such as intensive care
data by providing device integration of test results, medication information,
chronic diseases, demographic information, ICD diagnosis codes, and recent
intensive care patient data, not patient arrival or billing information.
Can Future Risky Diseases be Predicted?
By processing the HBYS data by Artificial Intelligence (AI), the risk of many diseases can be
predicted. The future course of the conditions and the chances that the patients will face in the
future can be expected.
Machine Learning (ML) algorithms were developed with HBYS data in the study to predict
whether a patient will have diabetes in the future or other disease risks. The symptoms recorded
and the ICD codes received by the patient are associated with the values obtained at each visit.
In addition, model development studies are carried out to predict diseases in the long term.
According to a study published in Cell Patterns, it is stated that Machine Learning (ML) is
used to connect patients’ HBYS data, including drugs and diagnostics, to measure disease risk.
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3. A team from NYU Langone Health analyzed HBYS data and found a strong correlation
between low oxygen levels and markers of inflammation in the blood of patients hospitalized
with COVID–19 and poor outcomes of COVID–19 disease.
In addition, researchers estimate cardiovascular disease risk using HBYS data with
Machine Learning (ML) tools. The study serves to diagnose heart disease earlier and promote
healthy lifestyles.
It is rapidly included in studies associated with the genome sequences of patients.
It does not seem possible to use HBYS data in this way.
It is stated in the studies that it does not seem possible to use the HBYS data as it is and that
applicable methods should be developed, such as making the data usable before using it in
predicting diseases with Machine Learning (ML) and removing unnecessary data.
The Ministry of Health, which controls big data in health, should pave the way for studies
on predicting diseases and encourage academicians and entrepreneurs who want to work on
this subject.
The first use of HBYS 20–30 years ago started for billing purposes. After that, the Media
application of the social security institution and the data for the decision–makers of the Ministry
of Health were decisive in HBYS.
After that, HBYS data should be structured for Machine Learning (ML) and Artificial Intelli-
gence (AI) applications that will be developed to prevent diseases and predict future disease
risks.
The HIMS data, which has been collected for about 30 years, will enable the development
of preventive treatments, reduce the treatment costs, and make Turkey a pioneer in Artificial
Intelligence (AI) technologies in health, with the studies to be carried out by technology entre-
preneurs and academics for the prediction and prevention of diseases.
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