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Subject: In this article, convolutional networks of one, two, and three dimensions are compared with respect to their ability to distinguish between the drawing tests produced by Parkinson's disease patients and healthy control subjects.…

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

A widely used test for the diagnosis of Parkinson's disease (PD) and Essential tremor (ET) is hand-drawn shapes,where the analysis is observationally performed by the examining neurologist. This method is subjective and is prone to bias…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Nabeel Seedat , Vered Aharonson , Ilana Schlesinger

Parkinson's disease (PD) is a slowly progressing neurodegenerative disease with early manifestation of motor signs. Recently, there has been a growing interest in developing automatic tools that can assess motor function in PD patients.…

Information Retrieval · Computer Science 2018-05-04 Liron Allerhand , Brit Youngmann , Elad Yom-Tov , David Arkadir

Parkinson's Disease (PD) is characterized by disorders in motor function such as freezing of gait, rest tremor, rigidity, and slowed and hyposcaled movements. Medication with dopaminergic medication may alleviate those motor symptoms,…

Computer Vision and Pattern Recognition · Computer Science 2018-08-09 Terry Taewoong Um , Franz Michael Josef Pfister , Daniel Christian Pichler , Satoshi Endo , Muriel Lang , Sandra Hirche , Urban Fietzek , Dana Kulić

The paper presents a novel approach, based on deep learning, for diagnosis of Parkinson's disease through medical imaging. The approach includes analysis and use of the knowledge extracted by Deep Convolutional and Recurrent Neural Networks…

Machine Learning · Computer Science 2019-11-26 James Wingate , Ilianna Kollia , Luc Bidaut , Stefanos Kollias

Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms. However, traditional diagnostic approaches may suffer from…

Machine Learning · Computer Science 2020-10-14 Jie Mei , Christian Desrosiers , Johannes Frasnelli

This paper represents a groundbreaking advancement in Parkinson disease (PD) research by employing a novel machine learning framework to categorize PD into distinct subtypes and predict its progression. Utilizing a comprehensive dataset…

Machine Learning · Computer Science 2024-06-12 Ashwin Ram

Motor dysfunction is a common sign of neurodegenerative diseases (NDs) such as Parkinson's disease (PD) and Alzheimer's disease (AD), but may be difficult to detect, especially in the early stages. In this work, we examine the behavior of a…

Neurons and Cognition · Quantitative Biology 2025-10-23 Thomas Thebaud , Anna Favaro , Casey Chen , Gabrielle Chavez , Laureano Moro-Velazquez , Ankur Butala , Najim Dehak

Parkinson's disease (PD) is a chronic neurodegenerative disease. It shows multiple motor symptoms such as tremor, bradykinesia, postural instability, freezing of gait (FoG). PD is currently diagnosed clinically through physical exam by…

Machine Learning · Computer Science 2026-04-21 Meheru Zannat

Parkinson's disease (PD) is a chronic neurodegenerative disease. Early diagnosis is essential to mitigate the progressive deterioration of patients' quality of life. The most characteristic motor symptoms are very mild in the early stages,…

Machine Learning · Computer Science 2026-01-27 Beatriz Pérez-Sánchez , Noelia Sánchez-Maroño , Miguel A. Díaz-Freire

Parkinson's Disease (PD) affects millions globally, impacting movement. Prior research utilized deep learning for PD prediction, primarily focusing on medical images, neglecting the data's underlying manifold structure. This work proposes a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Jun-En Ding , Chien-Chin Hsu , Feng Liu

At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together…

Machine Learning · Computer Science 2020-05-07 Afra Nawar , Farhan Rahman , Narayanan Krishnamurthi , Anirudh Som , Pavan Turaga

The stage and severity of Parkinson's disease (PD) is an important factor to consider for taking effective therapeutic decisions. Although the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) provides an…

Applications · Statistics 2018-05-30 R. Prashanth , Sumantra Dutta Roy

This paper presents the development of a new passive assistive handwriting device, which aims to stabilize the motion of people living with movement disorders. Many people living with conditions such as cerebral palsy, stroke, muscular…

Parkinson's Disease (PD) is a progressive neurodegenerative disorder that significantly impacts both motor and non-motor functions, including speech. Early and accurate recognition of PD through speech analysis can greatly enhance patient…

Numerical Analysis · Mathematics 2024-07-24 Niloofar Fadavi , Nazanin Fadavi

The automatic identification of medication states of Parkinson's disease (PD) patients can assist clinicians in monitoring and scheduling personalized treatments, as well as studying the effects of medication in alleviating the motor…

Changes in speech and language are among the first signs of Parkinson's disease (PD). Thus, clinicians have tried to identify individuals with PD from their voices for years. Doctors can leverage AI-based speech assessments to spot PD…

Sound · Computer Science 2023-12-06 Mahboobeh Parsapoor

This paper presents a new method for medical diagnosis of neurodegenerative diseases, such as Parkinson's, by extracting and using latent information from trained Deep convolutional, or convolutional-recurrent Neural Networks (DNNs). In…

Machine Learning · Computer Science 2019-01-24 Ilianna Kollia , Andreas-Georgios Stafylopatis , Stefanos Kollias

Recently proposed automatic pathological speech classification techniques use unsupervised auto-encoders to obtain a high-level abstract representation of speech. Since these representations are learned based on reconstructing the input,…

Audio and Speech Processing · Electrical Eng. & Systems 2021-07-22 Parvaneh Janbakhshi , Ina Kodrasi