Systematic review on ai-blockchain based e-healthcare records management systems
Electronic health records (EHRs) are digitally saved health records that provide information
about a person's health. EHRs are generally shared among healthcare stakeholders, and …
about a person's health. EHRs are generally shared among healthcare stakeholders, and …
Predictive data mining approaches in medical diagnosis: A review of some diseases prediction
R Ghorbani, R Ghousi - International Journal of Data and …, 2019 - m.growingscience.com
Due to the increasing technological advances in all fields, a considerable amount of data
has been collected to be processed for different purposes. Data mining is the process of …
has been collected to be processed for different purposes. Data mining is the process of …
Machine learning tools for long-term type 2 diabetes risk prediction
A steady rise has been observed in the percentage of elderly people who want and are still
able to contribute to society. Therefore, early retirement or exit from the labour market, due to …
able to contribute to society. Therefore, early retirement or exit from the labour market, due to …
Management of VUCA (Volatility, Uncertainty, Complexity and Ambiguity) Using machine learning techniques in industry 4.0 paradigm
With the fast advancement in technology and induction of information technology and
internet into various aspects of organizations, there has been both large scale of both …
internet into various aspects of organizations, there has been both large scale of both …
Utility of big data in predicting short-term blood glucose levels in type 1 diabetes mellitus through machine learning techniques
I Rodríguez-Rodríguez, I Chatzigiannakis… - Sensors, 2019 - mdpi.com
Machine learning techniques combined with wearable electronics can deliver accurate short-
term blood glucose level prediction models. These models can learn personalized glucose …
term blood glucose level prediction models. These models can learn personalized glucose …
Integration of machine learning algorithms and discrete-event simulation for the cost of healthcare resources
A healthcare resource allocation generally plays a vital role in the number of patients treated
(pnt) and the patient waiting time (wt) in healthcare institutions. This study aimed to estimate …
(pnt) and the patient waiting time (wt) in healthcare institutions. This study aimed to estimate …
[PDF][PDF] Analysis and prediction of diabetes diseases using machine learning algorithm: Ensemble approach
Machine learning techniques (MLT) are used to predict the medical datasets at an early
stage of safe human life. A huge medical datasets are accessible in different data …
stage of safe human life. A huge medical datasets are accessible in different data …
Efficient prediction of early-stage diabetes using XGBoost classifier with random forest feature selection technique
S Gündoğdu - Multimedia Tools and Applications, 2023 - Springer
Diabetes is one of the most common and serious diseases affecting human health. Early
diagnosis and treatment are vital to prevent or delay complications related to diabetes. An …
diagnosis and treatment are vital to prevent or delay complications related to diabetes. An …
[PDF][PDF] Analysis and prediction of diabetes mellitus using machine learning algorithm
Data mining techniques (DMTs) are very help full to predict the medical datasets at an early
stageto safe human life. Large amount of medical datasets areopen in different data sources …
stageto safe human life. Large amount of medical datasets areopen in different data sources …
Use of a K-nearest neighbors model to predict the development of type 2 diabetes within 2 years in an obese, hypertensive population
R Garcia-Carretero, L Vigil-Medina… - Medical & biological …, 2020 - Springer
Prediabetes is a type of hyperglycemia in which patients have blood glucose levels above
normal but below the threshold for type 2 diabetes mellitus (T2DM). Prediabetic patients are …
normal but below the threshold for type 2 diabetes mellitus (T2DM). Prediabetic patients are …