# End-to-End Parkinson Disease Diagnosis using Brain MR-Images by 3D-CNN

arXiv: https://arxiv.org/abs/1806.05233 · HTML: https://mlsanity.com/paper/1806.05233/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2018.

## Built on by (most cited first, 5 of 5)

- [Machine learning based disease diagnosis: A comprehensive review](https://mlsanity.com/paper/2112.15538/) (2021)
- [Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers](https://mlsanity.com/paper/2104.02066/) (2021)
- [Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning](https://mlsanity.com/paper/2203.02124/) (2022)
- [Early Diagnosis of Parkinsons Disease by Analyzing Magnetic Resonance Imaging Brain Scans and Patient Characteristics](https://mlsanity.com/paper/2201.04631/) (2022)
- [Identification of morphological fingerprint in perinatal brains using quasi-conformal mapping and contrastive learning](https://mlsanity.com/paper/2311.14955/) (2023)

## 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.