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 …

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 …

Parkinson's disease prediction using adaptive quantum computing

SR Swarna, A Kumar, P Dixit… - 2021 Third International …, 2021 - ieeexplore.ieee.org
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 …

Multi model implementation on general medicine prediction with quantum neural networks

SA Kumar, A Kumar, V Dutt… - 2021 Third International …, 2021 - ieeexplore.ieee.org
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 …

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 …

Heart failure detection using instance quantum circuit approach and traditional predictive analysis

S Alsubai, A Alqahtani, A Binbusayyis, M Sha… - Mathematics, 2023 - mdpi.com
The earlier prediction of heart diseases and appropriate treatment are important for
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 …

[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 …

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 …

[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 …