AI can Power Effective Diagnosis of Diabetes and Cardiovascular Diseases

Researchers from South Ural State University (SUSU) have come up with a newly developed model for highly effective diagnosis of diabetes and cardiovascular diseases using the technologies of the Internet of Things (IoT) and artificial intelligence (AI).

AI can Power Effective Diagnosis of Diabetes and Cardiovascular Diseases.

Image Credit: Gorodenkoff

The study was performed in collaboration with collaborators from Egypt, France and Spain. This work was financially supported by the Russian Ministry of Science and Higher Education. The new model for diagnosing diseases was explained in an article published in the acclaimed journal IEEE Access (Q1).

Smart Applications for Medicine

The new model was developed for the operation of digital applications and their application in medicine by Kumar Sachin, a senior researcher of the Department of System Programming and a PhD degree holder in machine learning. He achieved this in collaboration with researchers from other countries.

The latest developments in technologies like artificial intelligence, cloud computing and the Internet of Things have transformed the traditional healthcare system into a smart one.

Healthcare services could be considerably enhanced with the help of artificial intelligence and the Internet of Things. Since there is an availability of new techniques and scientific theories, huge amounts of digital data is produced and can be employed to make clinical applications using the Android OS.

Clinical applications are one of the latest information technology products. Smart healthcare is supposed to use simple, elegant and multitasking applications. These applications contribute to the evolution of the clinical model of medicine, that is, the transition from the standard treatment of the disease according to the scheme to the treatment of a specific patient.

Kumar Sachin, Study Senior Researcher, Department of System Programming, South Ural State University

Sachin continued, “There should be changes in the development of medical informatization from generalized medical data to regional medical data. Thus, the clinical management of the patient will become more person-centered rather than medical statistics.

Ideally, we should move from treating diseases to a preventive medical system. These changes are aimed at improving the healthcare system, which, in turn, improves knowledge in the field of medicine and implies a transition to intelligent medicine,” added Sachin.

Patients, doctors, as well as clinical and research centers have started showing their interest to offer improved medical services using the available new technologies. Also, there are various parameters to be kept in mind while these technologies are employed: clinical management, prognosis and treatment, disease prevention and surveillance, health decision making and medical research.

Each phase of smart healthcare involves the use of mobile Internet, 5G systems, big data, cloud computing, microelectronics and artificial intelligence, as well as intelligent biotechnologies. Portable devices could be utilized to track the patients’ health status when required.

There is an option for patients to receive clinical recommendations via virtual support and control devices remotely, and doctors will be able to make use of intelligent clinical decision-making systems to choose and enhance the quality of diagnostic procedures.

Collecting Information from All Devices

In day-to-day life, people are surrounded by devices that predominantly use the Internet of Things. They include portable ECG devices, smartwatches, fitness bracelets and smartphones, blood glucose meters and thermometers and blood pressure monitors. These gadgets help to track the level of heart rate, physical activity and blood glucose levels, they are also familiar and user-friendly. This eliminates the necessity to invent new technology for them.

The main concept of the researchers is to make a global application that can help gather data from various devices and translate it into a compatible format. Thus, the smartphone processes and arranges them. Based on the complicated data received, numerous medical recommendations will be created for one particular patient, considering his or her indicators.

The model we presented includes various stages: data collection, pre-processing, classification and parameter adjustment. Portable IoT devices and sensors allow you to collect data without hindrance, while artificial intelligence methods use them to diagnose diseases.

Kumar Sachin, Study Senior Researcher, Department of System Programming, South Ural State University

Based on these indicators, it is possible to determine how good the lifestyle of a patient with a particular disease is. The smartphone processes the data received via a Bluetooth connection with low power consumption and classifies it as healthy, within the normal range, or as unhealthy,” added Sachin.

The new model’s efficacy was verified using health data. When the experiments were in progress, the presented model achieved an ideal precision of 96.16% and 97.26% in the diagnosis of diabetes and heart disease, respectively. Therefore, the suggested model can be utilized as an ideal tool for diagnosing diseases for an intelligent healthcare system.

Journal Reference:

Mansour, R. F., et al. (2021) Artificial Intelligence and Internet of Things Enabled Disease Diagnosis Model for Smart Healthcare Systems. IEEE Access.

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