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 …
above certain limits. Over the last years, machine and deep learning techniques have been …
The state of quantum computing applications in health and medicine
FF Flöther - Research Directions: Quantum Technologies, 2023 - cambridge.org
Medicine, including fields in healthcare and life sciences, has seen a flurry of quantum-
related activities and experiments in the last few years (although biology and quantum …
related activities and experiments in the last few years (although biology and quantum …
Heart failure detection using quantum‐enhanced machine learning and traditional machine learning techniques for internet of artificially intelligent medical things
Quantum‐enhanced machine learning plays a vital role in healthcare because of its robust
application concerning current research scenarios, the growth of novel medical trials, patient …
application concerning current research scenarios, the growth of novel medical trials, patient …
[HTML][HTML] An assessment of machine learning models and algorithms for early prediction and diagnosis of diabetes using health indicators
Breakthroughs in healthcare analytics can help both the doctor and the patient. Analytics in
healthcare can help spot and diagnose diseases early on. Therefore, they can also be used …
healthcare can help spot and diagnose diseases early on. Therefore, they can also be used …
A quantum convolutional network and ResNet (50)-based classification architecture for the MNIST medical dataset
Biomedical image classification is crucial for both computer vision tasks and clinical care.
The conventional method requires a significant amount of time and effort for extracting and …
The conventional method requires a significant amount of time and effort for extracting and …
Machine learning models for classification and identification of significant attributes to detect type 2 diabetes
Abstract Type 2 Diabetes (T2D) is a chronic disease characterized by abnormally high blood
glucose levels due to insulin resistance and reduced pancreatic insulin production. The …
glucose levels due to insulin resistance and reduced pancreatic insulin production. The …
Quantum machine learning in healthcare: Developments and challenges
S Rani, PK Pareek, J Kaur, M Chauhan… - … on Integrated Circuits …, 2023 - ieeexplore.ieee.org
Machine learning is playing a very significant role to process voluminous data and its
classification in a variety of domains. Due to better performance and rapid development in …
classification in a variety of domains. Due to better performance and rapid development in …
Quantum machine learning applications in the biomedical domain: A systematic review
Quantum technologies have become powerful tools for a wide range of application
disciplines, which tend to range from chemistry to agriculture, natural language processing …
disciplines, which tend to range from chemistry to agriculture, natural language processing …
Quantum machine learning revolution in healthcare: a systematic review of emerging perspectives and applications
U Ullah, B Garcia-Zapirain - IEEE Access, 2024 - ieeexplore.ieee.org
Quantum computing (QC) stands apart from traditional computing systems by employing
revolutionary techniques for processing information. It leverages the power of quantum bits …
revolutionary techniques for processing information. It leverages the power of quantum bits …
[HTML][HTML] A robust predictive diagnosis model for diabetes mellitus using Shapley-incorporated machine learning algorithms
With the rapid advancement and integration of Artificial Intelligence (AI) in medicine, the
need for new developments and accuracy in Machine Learning (ML) models and algorithms …
need for new developments and accuracy in Machine Learning (ML) models and algorithms …