Mobile health in remote patient monitoring for chronic diseases: Principles, trends, and challenges
Chronic diseases are becoming more widespread. Treatment and monitoring of these
diseases require going to hospitals frequently, which increases the burdens of hospitals and …
diseases require going to hospitals frequently, which increases the burdens of hospitals and …
AI-assisted decision-making in healthcare: the application of an ethics framework for big data in health and research
Artificial intelligence (AI) is set to transform healthcare. Key ethical issues to emerge with this
transformation encompass the accountability and transparency of the decisions made by AI …
transformation encompass the accountability and transparency of the decisions made by AI …
End-to-end deep learning framework for coronavirus (COVID-19) detection and monitoring
Coronavirus (COVID-19) is a new virus of viral pneumonia. It can outbreak in the world
through person-to-person transmission. Although several medical companies provide …
through person-to-person transmission. Although several medical companies provide …
A drug prescription recommendation system based on novel DIAKID ontology and extensive semantic rules
Abstract According to the World Health Organization (WHO) data from 2000 to 2019, the
number of people living with Diabetes Mellitus and Chronic Kidney Disease (CKD) is …
number of people living with Diabetes Mellitus and Chronic Kidney Disease (CKD) is …
An ontology network for Diabetes Mellitus in Mexico
Background Medical experts in the domain of Diabetes Mellitus (DM) acquire specific
knowledge from diabetic patients through monitoring and interaction. This allows them to …
knowledge from diabetic patients through monitoring and interaction. This allows them to …
Prediction of prediabetes using fuzzy logic based association classification
AM Rajeswari, MS Sidhika… - 2018 Second …, 2018 - ieeexplore.ieee.org
Diabetes is one of the world's most common chronic disease. Prediabetes is the pre-phase
of diabetes, which slowly lead to type-2 diabetes. Early detection of diabetes prevents …
of diabetes, which slowly lead to type-2 diabetes. Early detection of diabetes prevents …
An enhanced diabetes mellitus prediction using feature selection-based type-2 fuzzy model
The diabetes mellitus has been known to be a serious illness and revered for its ability to
cause high mortality rate. This disease is famous among both youth and adult for its …
cause high mortality rate. This disease is famous among both youth and adult for its …
Classification of diabetic patients records using Naïve Bayes classifier
KS Thulasi, ES Ninu, KKM Shiva - 2017 2nd IEEE International …, 2017 - ieeexplore.ieee.org
Classifying the diabetic patients records based on archieved data is one of the
computational diagnosis method. In this paper we present the classification of diabetic …
computational diagnosis method. In this paper we present the classification of diabetic …
[HTML][HTML] Smart diabetic screening and managing software, a novel decision support system
Background: Diabetes is a serious chronic disease, and its increasing prevalence is a global
concern. If diabetes mellitus is left untreated, poor control of blood glucose may cause long …
concern. If diabetes mellitus is left untreated, poor control of blood glucose may cause long …
Detecting Ineffective Self-Management in Diabetic Patients: A Data Mining Perspective
Chronic conditions are long-term diseases that inflict limitations to patient's life-style. These
conditions can be controlled but not fully cured. Therefore, effective self-management and …
conditions can be controlled but not fully cured. Therefore, effective self-management and …