Machine learning for diabetes clinical decision support: a review

A Tuppad, SD Patil - Advances in Computational Intelligence, 2022 - Springer
Type 2 diabetes has recently acquired the status of an epidemic silent killer, though it is non-
communicable. There are two main reasons behind this perception of the disease. First, a …

[HTML][HTML] Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods

N Ayoobi, D Sharifrazi, R Alizadehsani, A Shoeibi… - Results in physics, 2021 - Elsevier
The first known case of Coronavirus disease 2019 (COVID-19) was identified in December
2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and …

Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture

LP Joseph, EA Joseph, R Prasad - Computers in Biology and Medicine, 2022 - Elsevier
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …

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 …

Demand forecasting model for time-series pharmaceutical data using shallow and deep neural network model

R Rathipriya, AA Abdul Rahman… - Neural Computing and …, 2023 - Springer
Demand forecasting is a scientific and methodical assessment of future demand for a critical
product. The effective Demand Forecast Model (DFM) enables pharmaceutical companies to …

Deep LSTM model for diabetes prediction with class balancing by SMOTE

SA Alex, NZ Jhanjhi, M Humayun, AO Ibrahim… - Electronics, 2022 - mdpi.com
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 …

A deep learning approach for real-time crash prediction using vehicle-by-vehicle data

F Basso, R Pezoa, M Varas, M Villalobos - Accident Analysis & Prevention, 2021 - Elsevier
In road safety, real-time crash prediction may play a crucial role in preventing such traffic
events. However, much of the research in this line generally uses data aggregated every five …

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 …

A novel proposal for deep learning-based diabetes prediction: converting clinical data to image data

MF Aslan, K Sabanci - Diagnostics, 2023 - mdpi.com
Diabetes, one of the most common diseases worldwide, has become an increasingly global
threat to humans in recent years. However, early detection of diabetes greatly inhibits the …

Remaining useful life prediction of lithium-ion battery via a sequence decomposition and deep learning integrated approach

Z Chen, L Chen, W Shen, K Xu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The remaining useful life (RUL) prediction of Lithium-ion batteries (LIBs) is of great
importance to the health management of electric vehicles and hybrid electric vehicles …