End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN
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Abstract (arXiv)
In this work, we use a deep learning framework for simultaneous classification and regression of Parkinson disease diagnosis based on MR-Images and personal information (i.e. age, gender). We intend to facilitate and increase the confidence in Parkinson disease diagnosis through our deep learning framework.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jun 2018.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1.
5 papers.
- 2021Machine learning based disease diagnosis: A comprehensive reviewcited by 30
- 2021Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifierscited by 2
- 2022Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learningcited by 2
- 2022Early Diagnosis of Parkinsons Disease by Analyzing Magnetic Resonance Imaging Brain Scans and Patient Characteristicscited by 0
- 2023Identification of morphological fingerprint in perinatal brains using quasi-conformal mapping and contrastive learningcited by 0
- 2023Identification of morphological fingerprint in perinatal brains using quasi-conformal mapping and contrastive learning25 Nov 2023
- 2022Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning4 Mar 2022
- 2022Early Diagnosis of Parkinsons Disease by Analyzing Magnetic Resonance Imaging Brain Scans and Patient Characteristics12 Jan 2022
- 2021Machine learning based disease diagnosis: A comprehensive review31 Dec 2021
- 2021Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers6 Apr 2021