[PDF][PDF] A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learning
Research Article A Smart Healthcare Recommendation System for Multidisciplinary Diabetes
Patients with Data Fusion Based on Deep Page 1 Research Article A Smart Healthcare …
Patients with Data Fusion Based on Deep Page 1 Research Article A Smart Healthcare …
Deep Neural Network Based Ensemble learning Algorithms for the healthcare system (diagnosis of chronic diseases)
J Abdollahi, B Nouri-Moghaddam… - arXiv preprint arXiv …, 2021 - arxiv.org
learning algorithms. In this paper, we review the classification algorithms used in the health
care system (chronic diseases) and present the neural network-based Ensemble learning …
care system (chronic diseases) and present the neural network-based Ensemble learning …
[HTML][HTML] DeepReco: deep learning based health recommender system using collaborative filtering
In today's digital world healthcare is one core area of the medical domain. A healthcare
system is required to analyze a large amount of patient data which helps to derive insights …
system is required to analyze a large amount of patient data which helps to derive insights …
Intelligence-based health recommendation system using big data analytics
In today's digital world, healthcare is one of the core areas in the medical domain. A
healthcare system is required to analyze a large amount of patient data, which helps to …
healthcare system is required to analyze a large amount of patient data, which helps to …
Deep learning for diabetes: a systematic review
Diabetes is a chronic metabolic disorder that affects an estimated 463 million people
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …
worldwide. Aiming to improve the treatment of people with diabetes, digital health has been …
CNN-RNN based intelligent recommendation for online medical pre-diagnosis support
The rapidly developed Health 2.0 technology has provided people with more opportunities
to conduct online medical consultation than ever before. Understanding contexts within …
to conduct online medical consultation than ever before. Understanding contexts within …
eDiaPredict: an ensemble-based framework for diabetes prediction
Medical systems incorporate modern computational intelligence in healthcare. Machine
learning techniques are applied to predict the onset and reoccurrence of the disease …
learning techniques are applied to predict the onset and reoccurrence of the disease …
Predicting diabetes diseases using mixed data and supervised machine learning algorithms
O Daanouni, B Cherradi, A Tmiri - … of the 4th International Conference on …, 2019 - dl.acm.org
Diabetes is considered as one of the deadliest and chronic diseases in several countries. All
of them are working to prevent this disease at early stage by diagnosing and predicting the …
of them are working to prevent this disease at early stage by diagnosing and predicting the …
Prediction of diabetes empowered with fused machine learning
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 …
of the most dangerous diseases all over the world. In modern lifestyles, sugar and fat are …
Deep belief neural network for 5G diabetes monitoring in big data on edge IoT
The diabetes is a critical disease from the small children to old age people. Due to improper
diet and physical activities of the living population, obesity becomes prevalent in young …
diet and physical activities of the living population, obesity becomes prevalent in young …