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Quantum machine learning revolution in healthcare: a systematic review of emerging perspectives and applications
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 …
Quantum machine learning in healthcare: Developments and challenges
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 …
Parkinson's disease prediction using adaptive quantum computing
Adaptability is the most generous thing we need to acquire to solve any kind of prediction
model design and implementation. Dementia is the most dangerous disease which will …
model design and implementation. Dementia is the most dangerous disease which will …
Multi model implementation on general medicine prediction with quantum neural networks
Medical is the large-scale repository where there is more chances to create a new model in
the zone of prediction. The proposed methodology mentioned in this article speaks about …
the zone of prediction. The proposed methodology mentioned in this article speaks about …
Self-health analysis with two step histogram based procedure using machine learning
SA Kumar, H Kumar, V Dutt… - 2021 Third International …, 2021 - ieeexplore.ieee.org
Machine learning is the critical tool in the future for prediction in the real-time to analyze the
self-health of the person. The self-health is the motivation for the patient who is suffering …
self-health of the person. The self-health is the motivation for the patient who is suffering …
Heart failure detection using instance quantum circuit approach and traditional predictive analysis
The earlier prediction of heart diseases and appropriate treatment are important for
preventing cardiac failure complications and reducing the mortality rate. The traditional …
preventing cardiac failure complications and reducing the mortality rate. The traditional …
Application of machine learning in rheumatoid arthritis diseases research: review and future directions
AH Patil Kose, K Mangaonkar - Combinatorial Chemistry & High …, 2023 - benthamdirect.com
Rheumatoid arthritis (RA) is a chronic, destructive condition that affects and destroys the
joints of the hand, fingers, and legs. Patients may forfeit the ability to conduct a normal …
joints of the hand, fingers, and legs. Patients may forfeit the ability to conduct a normal …
[PDF][PDF] A study of multicollinearity detection and rectification under missing values
AU Ahmad, UV Balakrishnan… - Turkish Journal of …, 2021 - researchgate.net
Today missing data is becoming more challenging than ever before, this is due to the rapid
advancement in technology of computations couple with the current statistical techniques …
advancement in technology of computations couple with the current statistical techniques …
Pre-Trained Deep Learning-Based Approaches for Eye Disease Detection
P Kumar, S Bhandari, V Dutt - 2023 International Conference …, 2023 - ieeexplore.ieee.org
This study primarily examines how well four pretrained deep learning models perform in
identifying eye disorders using four metrics we developed: recall, precision, accuracy, and …
identifying eye disorders using four metrics we developed: recall, precision, accuracy, and …
[PDF][PDF] Knowledge discovery and data mining healthcare
A Parihar, S Sharma - International Journal of Information …, 2020 - researchgate.net
The dataset in the knowledge discovery database is frightened by the advancement of
strategies and procedures for utilizing information. Data mining is one of the most important …
strategies and procedures for utilizing information. Data mining is one of the most important …