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[HTML][HTML] A review on deep learning models for forecasting time series data of solar irradiance and photovoltaic power
Presently, deep learning models are an alternative solution for predicting solar energy
because of their accuracy. The present study reviews deep learning models for handling …
because of their accuracy. The present study reviews deep learning models for handling …
Weather forecasting for renewable energy system: a review
Energy crisis and climate change are the major concerns which has led to a significant
growth in the renewable energy resources which includes mainly the solar and wind power …
growth in the renewable energy resources which includes mainly the solar and wind power …
[HTML][HTML] Diabetes detection using deep learning algorithms
Diabetes is a metabolic disease affecting a multitude of people worldwide. Its incidence
rates are increasing alarmingly every year. If untreated, diabetes-related complications in …
rates are increasing alarmingly every year. If untreated, diabetes-related complications in …
[HTML][HTML] Deep LSTM model for diabetes prediction with class balancing by SMOTE
Diabetes is an acute disease that happens when the pancreas cannot produce enough
insulin. It can be fatal if undiagnosed and untreated. If diabetes is revealed early enough, it …
insulin. It can be fatal if undiagnosed and untreated. If diabetes is revealed early enough, it …
An optimization-based diabetes prediction model using CNN and Bi-directional LSTM in real-time environment
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 …
levels in the blood. A good diagnosis of diabetes may make a person's life better; otherwise …
Deep convolutional neural networks with ensemble learning and transfer learning for automated detection of gastrointestinal diseases
Q Su, F Wang, D Chen, G Chen, C Li, L Wei - Computers in Biology and …, 2022 - Elsevier
Gastrointestinal (GI) diseases are serious health threats to human health, and the related
detection and treatment of gastrointestinal diseases place a huge burden on medical …
detection and treatment of gastrointestinal diseases place a huge burden on medical …
[HTML][HTML] Current techniques for diabetes prediction: review and case study
Diabetes is one of the most common diseases worldwide. Many Machine Learning (ML)
techniques have been utilized in predicting diabetes in the last couple of years. The …
techniques have been utilized in predicting diabetes in the last couple of years. The …
[HTML][HTML] Using recurrent neural networks for predicting type-2 diabetes from genomic and tabular data
The development of genomic technology for smart diagnosis and therapies for various
diseases has lately been the most demanding area for computer-aided diagnostic and …
diseases has lately been the most demanding area for computer-aided diagnostic and …
A deep neural network with modified random forest incremental interpretation approach for diagnosing diabetes in smart healthcare
Artificial intelligence (AI) applications based on deep learning for diagnosing type-II diabetes
are sometimes difficult to understand and communicate even as patients are eager to …
are sometimes difficult to understand and communicate even as patients are eager to …
A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram
The success of deep learning over the traditional machine learning techniques in handling
artificial intelligence application tasks such as image processing, computer vision, object …
artificial intelligence application tasks such as image processing, computer vision, object …