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In this work, we explore various neural network architectures using Magnetic Resonance (MR) T1 images of the brain to identify Parkinson's Disease (PD), which is one of the most common neurodegenerative and movement disorders. We propose…

Image and Video Processing · Electrical Eng. & Systems 2020-07-27 Tahjid Ashfaque Mostafa , Irene Cheng

Characterising the heterogeneous presentation of Parkinson's disease (PD) requires integrating biological and clinical markers within a unified predictive framework. While multimodal data provide complementary information, many existing…

Machine Learning · Computer Science 2026-01-05 Dristi Datta , Tanmoy Debnath , Minh Chau , Manoranjan Paul , Gourab Adhikary , Md Geaur Rahman

Although neural networks have proven very successful in a number of medical image analysis applications, their use remains difficult when targeting subtle tasks such as the identification of barely visible brain lesions, especially given…

Image and Video Processing · Electrical Eng. & Systems 2021-10-26 Verónica Muñoz-Ramírez , Nicolas Pinon , Florence Forbes , Carole Lartizen , Michel Dojat

Parkinson's Disease PD is a progressive neurodegenerative disorder that affects motor and cognitive functions with early diagnosis being critical for effective clinical intervention Electroencephalography EEG offers a noninvasive and…

Parkinson's disease (PD) is a neuro-degenerative disorder that affects movement, speech, and coordination. Timely diagnosis and treatment can improve the quality of life for PD patients. However, access to clinical diagnosis is limited in…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Md. Zarif Ul Alam , Md Saiful Islam , Ehsan Hoque , M Saifur Rahman

Oculomotor alterations constitute a promising biomarker to detect and characterize Parkinson's disease (PD), even in prodromal stages. Currently, only global and simplified eye movement trajectories are employed to approximate the complex…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Juan Niño , Luis Guayacán , Santiago Gómez , Fabio Martínez

As the number of automatic tools based on machine learning (ML) and resting-state electroencephalography (rs-EEG) for Parkinson's disease (PD) detection keeps growing, the assessment of possible exacerbation of health disparities by means…

Signal Processing · Electrical Eng. & Systems 2023-03-14 Anna Kurbatskaya , Alberto Jaramillo-Jimenez , John Fredy Ochoa-Gomez , Kolbjørn Brønnick , Alvaro Fernandez-Quilez

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and affects around 1% of the (60+ years old) elderly population in industrial nations. More than 80% of PD patients suffer from motor symptoms, which…

Parkinson's disease is a neurodegenerative disorder that can be very tricky to diagnose and treat. Such early symptoms can include tremors, wheezy breathing, and changes in voice quality as critical indicators of neural damage. Notably,…

Sound · Computer Science 2025-11-20 Abishek Karthik , Pandiyaraju V , Dominic Savio M , Rohit Swaminathan S

People with Parkinson's disease must be regularly monitored by their physician to observe how the disease is progressing and potentially adjust treatment plans to mitigate the symptoms. Monitoring the progression of the disease through a…

Audio and Speech Processing · Electrical Eng. & Systems 2022-05-25 Mohammadreza Iman , Amy Giuntini , Hamid Reza Arabnia , Khaled Rasheed

How people look at visual information reveals fundamental information about themselves, their interests and their state of mind. While previous visual attention models output static 2-dimensional saliency maps, saccadic models aim to…

Computer Vision and Pattern Recognition · Computer Science 2017-02-16 Olivier Le Meur , Antoine Coutrot , Zhi Liu , Adrien Le Roch , Andrea Helo , Pia Rama

There is great interest in developing radiological classifiers for diagnosis, staging, and predictive modeling in progressive diseases such as Parkinson's disease (PD), a neurodegenerative disease that is difficult to detect in its early…

We present an artificial intelligence system to remotely assess the motor performance of individuals with Parkinson's disease (PD). Participants performed a motor task (i.e., tapping fingers) in front of a webcam, and data from 250 global…

Falls are detrimental to people with Parkinson's Disease (PD) because of the potentially severe consequences to the patients' quality of life. While many studies have attempted to predict falls/non-falls, this study aimed to determine…

Applications · Statistics 2019-10-07 Sarini Abdullah , James McGree , Nicole White , Kerrie Mengersen , Graham Kerr

Parkinson's disease (PD) is a common and complex neurodegenerative disorder with 5 stages in the Hoehn and Yahr scaling. Given the heterogeneity of PD, it is challenging to classify early stages 1 and 2 and detect brain function…

Neurons and Cognition · Quantitative Biology 2022-07-22 Xueqi Guo , Sule Tinaz , Nicha C. Dvornek

Parkinson's disease is a neurodegenerative disease that can affect a person's movement, speech, dexterity, and cognition. Clinicians primarily diagnose Parkinson's disease by performing a clinical assessment of symptoms. However,…

Neurons and Cognition · Quantitative Biology 2018-11-16 Patrick Schwab , Walter Karlen

Parkinson's disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0.1-1 %, and an annual incidence between 1.3-2.0/10000 inhabitants. The mean age at diagnosis of PD is 55 and…

Parkinson's disease (PD) presents a growing global challenge, affecting over 10 million individuals, with prevalence expected to double by 2040. Early diagnosis remains difficult due to the late emergence of motor symptoms and limitations…

Machine Learning · Computer Science 2025-10-21 Arianna Francesconi , Donato Cappetta , Fabio Rebecchi , Paolo Soda , Valerio Guarrasi , Rosa Sicilia

Parkinson's disease is a widespread neurodegenerative condition necessitating early diagnosis for effective intervention. This paper introduces an innovative method for diagnosing Parkinson's disease through the analysis of human EEG…

Signal Processing · Electrical Eng. & Systems 2024-05-03 Maryam Allahbakhshi , Aylar Sadri , Seyed Omid Shahdi

In this paper, we propose a novel deep learning method based on a new Hybrid ConvNet-Transformer architecture to detect and stage Parkinson's disease (PD) from gait data. We adopt a two-step approach by dividing the problem into two…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Safwen Naimi , Wassim Bouachir , Guillaume-Alexandre Bilodeau