[HTML][HTML] Smart healthcare disease diagnosis and patient management: Innovation, improvement and skill development

A Ray, AK Chaudhuri - Machine Learning with Applications, 2021 - Elsevier
Data mining (DM) is an instrument of pattern detection and retrieval of knowledge from a
large quantity of data. Many robust early detection services and other health-related …

Prediction of diabetes empowered with fused machine learning

U Ahmed, GF Issa, MA Khan, S Aftab, MF Khan… - IEEE …, 2022 - ieeexplore.ieee.org
In the medical field, it is essential to predict diseases early to prevent them. Diabetes is one
of the most dangerous diseases all over the world. In modern lifestyles, sugar and fat are …

An optimization-based diabetes prediction model using CNN and Bi-directional LSTM in real-time environment

P Madan, V Singh, V Chaudhari, Y Albagory… - Applied Sciences, 2022 - mdpi.com
Featured Application Diabetes is a common chronic disorder defined by excessive glucose
levels in the blood. A good diagnosis of diabetes may make a person's life better; otherwise …

Intelligent machine learning approach for effective recognition of diabetes in E-healthcare using clinical data

AU Haq, JP Li, J Khan, MH Memon, S Nazir, S Ahmad… - Sensors, 2020 - mdpi.com
Significant attention has been paid to the accurate detection of diabetes. It is a big challenge
for the research community to develop a diagnosis system to detect diabetes in a successful …

Performance evaluation of different machine learning methods and deep-learning based convolutional neural network for health decision making

AK Sahoo, C Pradhan, H Das - Nature inspired computing for data science, 2020 - Springer
Now-a-days modern technology is used for health management and diagnostic strategy in
the health sector. Machine learning usually helps in decision making for health issues using …

Diagnosis of diabetes using machine learning algorithms

FA Khaleel, AM Al-Bakry - Materials Today: Proceedings, 2023 - Elsevier
One of the chronic diseases is Diabetes, Diabetes is a metabolic disorder category caused
by continued high levels of blood sugar. It is regarded as one of the most deadly diseases in …

A methodological approach for predicting COVID-19 epidemic using EEMD-ANN hybrid model

N Hasan - Internet of things, 2020 - Elsevier
Predicting the Coronavirus epidemic, popularly known as COVID-19, that has been explored
more than 200 countries and already declared as a pandemic by the World Health …

Machine and deep learning techniques for the prediction of diabetics: a review

SKS Modak, VK Jha - Multimedia Tools and Applications, 2024 - Springer
Diabetes has become one of the significant reasons for public sickness and death in
worldwide. By 2019, diabetes had affected more than 463 million people worldwide …

Machine learning regression models for prediction of multiple ionospheric parameters

MC Iban, E Şentürk - Advances in Space Research, 2022 - Elsevier
The variation of the ionospheric parameters has a crucial role in space weather,
communication, and navigation applications. In this research, we analyze the prediction …

IoT Based Smart Home: A Machine Learning Approach

MKI Shafi, MR Sultan, SMM Rahman… - … on Computer and …, 2021 - ieeexplore.ieee.org
Smart home is slowly but steadily becoming a part of our daily life in today's world. IoT
provides another dimension to it, and this should not be surprising that there are more IoT …