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Diabetes presents a significant public health issue for Native Americans, exacerbated by cultural nuances often ignored by conventional healthcare. To address this, we introduce a mobile app designed with the cultural context of Native American populations in mind. The app’s development followed participatory design principles, with direct input from Native American stakeholders through focus groups…

Diabetes Mellitus Type 2 is a chronic disorder that affects the way the body metabolizes sugar (glucose) in the blood and depends on a combination of risk factors, such as genes and lifestyle. Although certain risk factors such as family history, age, or ethnicity cannot be changed, those related to diet, physical activity, and weight…

This research shows the study carried out on the Health Related to Quality of Life (HRQL) focuses on aspects related to the perception of health experienced and declared by the person, in different dimensions such as physical, mental, social, general perception of health and satisfaction achieved measured at different levels; the objective of the study…

Diabetes is a condition of the body in which blood sugar level is higher than the normal average value. It is considered as a major cause of morbidity worldwide. According to the data reported in 2015,420 million people had diabetes worldwide, type 2 diabetes account for 85% of these cases. This shows 9.2% of the…

In research project, efficiency comparison study in prediction of normalization with data mining classification. The purpose of the research was to compare three normalization methods in term of classification accuracy that the normalized data provided: Z-Score, Decimal Scaling and Statistical Column. The six known classifications: K-Nearest Neighbor, Decision Tree, Artificial Neural Network, Support Vector Machine,…

Cardiovascular diseases are the group of conditions produced in the heart or blood vessels. This is one of the main causes of death in Peru and the world, produced mostly by non-communicable diseases and harmful habits, which makes it an extremely predictable disease. These factors include body mass index, smoking, diabetes, age, blood pressure, total…

Day to day huge medical data have been accumulating for diabetic diseases. The complexity of storing, processing ,analyzing and predicting the data related to diabetics is not so easy for healthcare professionals .The prediction of accurate results also has the limitation due to scale of data increasing worldwide for patients, symptoms and test results .In…

Objectives: Describe the clinical characteristics and home care of patients diagnosed with COVID-19 in a Primary Healthcare Facility of the “Mi Peru” district, in the Callao Region, Peru. Materials and methods: Observational and descriptive cross-sectional study. A total of 84 subjects with positive results for Rapid Test IgM / IgG or molecular test (RT-PCR) participated.…

This paper proposes a closed association rule generation technique to investigate the association patterns of diseases that are frequent co-occurrence. Diseases records of 5,000 patients are studied to find the association patterns of disease co-occurrence. The CHARM algorithm is adapted to find frequent diseases that can cover all-important patterns with a small number. Then the…

With recent advancements in medical filed, the quantity of healthcare care data is increasing at a faster rate. Medical data classification is considered as a major research topic and numerous research works have been already existed in the literature. Presently, deep learning (DL) models offers an efficient method for developing a dedicated model to determine…

The human gut environment can contain hundreds to thousands bacterial species which are proven that they are associated with various diseases. Although Machine learning has been supporting and developing metagenomic researches to obtain great achievements in personalized medicine approaches to improve human health, we still face overfitting issues in Bioinformatics tasks related to metagenomic data…

Data mining is recognized as an effective technique for extracting and retrieving valuable information or decision from the vast available data. Because of the nature of the functionality of medical centers and hospitals, their data centers contain a collection of valuable information about their patients. By properly processing these data, different applications can be developed…

Chronic diseases such as heart disease, cancer, diabetes, and asthma continue to increase in the general public within the modern era. With careful observation of the symptoms potential diseases may be detected early and managed properly. For that to happen, the awareness of the symptoms and proper knowledge about the diseases may be needed for…