ChemicalQDeviceAlzheimer's Disease Neuroradiology and Quantum
Dear Healthcare Colleague, my name is Kevin Kawchak, and I am the Founder CEO of ChemicalQDevice. Today is February 10th, 2023 for "Alzheimer's Disease Neuroradiology and Quantum-Classical Hybrid Methods"
Promising research has been performed regarding hybrid quantum-classical approaches for Alzheimer's Disease Classification. In specific, conventional Convolutional neural networks such as ResNet and AlexNet have been utilized alongside Quantum Variational Circuits that run on quantum simulators.
The 3 papers were published between February 2022 and January 2023 that utilize MR Neuroimages from Kaggle or ADNI that were trained and tested. Feature Vector processing was performed, and was further reduced to experience quantum effects of superpositioning and entanglement prior to image classification. [1-3]
The January 2023 Shahwar et al. paper Feature Vector Dimensions and Number of Epochs compared to the other papers were larger, and used the AlexNet model. Binary classification accuracy was 96% when quantum methods were incorporated, compared to 91.9% for the author's classical only methods.
The 96% binary classification accuracy using classical and quantum methods represents the author's second approach with quantum, but this time using ADNI brain images instead of the Kaggle database. Other ADNI conventional studies included a 2018 Multimodal Convolutional Neural Network model with binary classification at 93.3% accuracy. In addition, Other authors in 2021 used a DemNet model with 4 classifications and 95.2% accuracy. [4-5]
Industry leaders are further Progressing quantum for medical imaging. A QC Ware Roche paper stated that Ion trap quantum computers are appropriate for advantage, due to All to All connectivity in a Fully Connect Layer. The paper mentioned that authors performed over 1 Billion probabilistic shots between quantum simulators and real hardware to better understand the performance of results. [6]
Strangeworks and Deloitte have collaborated to advance understanding advantages of classical methods vs. quantum simulator vs. quantum hardware. In addition, the authors explored preliminary error mitigation methods in imaging. [7]
Prospective medical imaging benefit utilizing larger datasets and models in hybrid studies is a function of the many organizations continuing to advance real quantum computers. National Science Foundation forecasts a practical quantum computer by their funded projects in 2023. The February 2023 TIME Magazine features a Real quantum computer on the cover with the caption "The future of computing is here". Lastly, an Ion-trap quantum computer manufacturing facility has been announced by IonQ for the First half of 2024. [8-10]
References are available in the comments below. Have a productive rest of your day.
Smile at end!
2/10/23 "Alzheimer's Disease Neuroradiology and Quantum-Classical Hybrid Methods" References[1] https://www.mdpi.com/2079-9292/11/5/721#B2-electronics-11-00721[2] https://arxiv.org/pdf/2301.12505.pdf[3] https://www.mdpi.com/2227-7390/11/2/376#B9-mathematics-11-00376[4] https://link.springer.com/article/10.1007/s12021-018-9370-4 [5] https://ieeexplore.ieee.org/abstract/document/9459692[6] https://arxiv.org/pdf/2109.01831.pdf [7] https://arxiv.org/ftp/arxiv/papers/2212/2212.08693.pdf[8] https://nsf.gov/news/factsheets/Factsheet_Quantum-proof7_508.pdf [9] https://time.com/6249784/quantum-computing-revolution/[10] https://ionq.com/news/ionq-to-open-first-quantum-computing-manufacturing-facility-in-the-u-s
Created by Kevin Kawchak Founder CEO ChemicalQDevice2023 San Diego, CaliforniaHealthcare Innovation
Promising research has been performed regarding hybrid quantum-classical approaches for Alzheimer's Disease Classification. In specific, conventional Convolutional neural networks such as ResNet and AlexNet have been utilized alongside Quantum Variational Circuits that run on quantum simulators.
The 3 papers were published between February 2022 and January 2023 that utilize MR Neuroimages from Kaggle or ADNI that were trained and tested. Feature Vector processing was performed, and was further reduced to experience quantum effects of superpositioning and entanglement prior to image classification. [1-3]
The January 2023 Shahwar et al. paper Feature Vector Dimensions and Number of Epochs compared to the other papers were larger, and used the AlexNet model. Binary classification accuracy was 96% when quantum methods were incorporated, compared to 91.9% for the author's classical only methods.
The 96% binary classification accuracy using classical and quantum methods represents the author's second approach with quantum, but this time using ADNI brain images instead of the Kaggle database. Other ADNI conventional studies included a 2018 Multimodal Convolutional Neural Network model with binary classification at 93.3% accuracy. In addition, Other authors in 2021 used a DemNet model with 4 classifications and 95.2% accuracy. [4-5]
Industry leaders are further Progressing quantum for medical imaging. A QC Ware Roche paper stated that Ion trap quantum computers are appropriate for advantage, due to All to All connectivity in a Fully Connect Layer. The paper mentioned that authors performed over 1 Billion probabilistic shots between quantum simulators and real hardware to better understand the performance of results. [6]
Strangeworks and Deloitte have collaborated to advance understanding advantages of classical methods vs. quantum simulator vs. quantum hardware. In addition, the authors explored preliminary error mitigation methods in imaging. [7]
Prospective medical imaging benefit utilizing larger datasets and models in hybrid studies is a function of the many organizations continuing to advance real quantum computers. National Science Foundation forecasts a practical quantum computer by their funded projects in 2023. The February 2023 TIME Magazine features a Real quantum computer on the cover with the caption "The future of computing is here". Lastly, an Ion-trap quantum computer manufacturing facility has been announced by IonQ for the First half of 2024. [8-10]
References are available in the comments below. Have a productive rest of your day.
Smile at end!
2/10/23 "Alzheimer's Disease Neuroradiology and Quantum-Classical Hybrid Methods" References[1] https://www.mdpi.com/2079-9292/11/5/721#B2-electronics-11-00721[2] https://arxiv.org/pdf/2301.12505.pdf[3] https://www.mdpi.com/2227-7390/11/2/376#B9-mathematics-11-00376[4] https://link.springer.com/article/10.1007/s12021-018-9370-4 [5] https://ieeexplore.ieee.org/abstract/document/9459692[6] https://arxiv.org/pdf/2109.01831.pdf [7] https://arxiv.org/ftp/arxiv/papers/2212/2212.08693.pdf[8] https://nsf.gov/news/factsheets/Factsheet_Quantum-proof7_508.pdf [9] https://time.com/6249784/quantum-computing-revolution/[10] https://ionq.com/news/ionq-to-open-first-quantum-computing-manufacturing-facility-in-the-u-s
Created by Kevin Kawchak Founder CEO ChemicalQDevice2023 San Diego, CaliforniaHealthcare Innovation