Machine-learning-based disease diagnosis: A comprehensive review

MM Ahsan, SA Luna, Z Siddique - Healthcare, 2022 - mdpi.com
Globally, there is a substantial unmet need to diagnose various diseases effectively. The
complexity of the different disease mechanisms and underlying symptoms of the patient …

Machine learning and deep learning predictive models for type 2 diabetes: a systematic review

L Fregoso-Aparicio, J Noguez, L Montesinos… - Diabetology & metabolic …, 2021 - Springer
Diabetes Mellitus is a severe, chronic disease that occurs when blood glucose levels rise
above certain limits. Over the last years, machine and deep learning techniques have been …

A comprehensive review of machine learning techniques on diabetes detection

T Sharma, M Shah - Visual Computing for Industry, Biomedicine, and Art, 2021 - Springer
Diabetes mellitus has been an increasing concern owing to its high morbidity, and the
average age of individual affected by of individual affected by this disease has now …

A survey on deep learning for time-series forecasting

A Mahmoud, A Mohammed - Machine learning and big data analytics …, 2021 - Springer
Deep learning, one of the most remarkable techniques of machine learning, has been a
major success in many fields, including image processing, speech recognition, and text …

Deep learning for time series forecasting: Advances and open problems

A Casolaro, V Capone, G Iannuzzo, F Camastra - Information, 2023 - mdpi.com
A time series is a sequence of time-ordered data, and it is generally used to describe how a
phenomenon evolves over time. Time series forecasting, estimating future values of time …

Machine-Learning-Based Prediction Modelling in Primary Care: State-of-the-Art Review

AH El-Sherbini, HU Hassan Virk, Z Wang… - Ai, 2023 - mdpi.com
Primary care has the potential to be transformed by artificial intelligence (AI) and, in
particular, machine learning (ML). This review summarizes the potential of ML and its …

Agree to disagree: When deep learning models with identical architectures produce distinct explanations

M Watson, BAS Hasan… - Proceedings of the …, 2022 - openaccess.thecvf.com
Deep Learning of neural networks has progressively become more prominent in healthcare
with models reaching, or even surpassing, expert accuracy levels. However, these success …

[HTML][HTML] A robust deep neural network framework for the detection of diabetes

OR Shahin, HH Alshammari, AA Alzahrani… - Alexandria Engineering …, 2023 - Elsevier
Significant developments occurred in numerous industries and fields during the digital age
(1997–2006). One industry that has seen similar changes is the healthcare sector. Big data …

[HTML][HTML] A comparative analysis on diagnosis of diabetes mellitus using different approaches–A survey

F Anwar, MY Ejaz, A Mosavi - Informatics in Medicine Unlocked, 2020 - Elsevier
Diabetes Mellitus is commonly known as diabetes. It is one of the most chronic diseases as
the World Health Organization (WHO) report shows that the number of diabetes patients has …

CausalBG: Causal recurrent neural network for the blood glucose inference with IoT platform

M He, W Gu, Y Kong, L Zhang… - IEEE Internet of …, 2019 - ieeexplore.ieee.org
Predicting blood glucose concentration facilitates timely preventive measures against health
risks induced by abnormal glucose events. Advances in IoT devices, such as continuous …