Translational Informatics for Parkinson’s Disease: from Big Biomedical Data to Small Actionable Alterations

This paper describes an advanced form of pseudonymisation in a large cohort study on Parkinson’s disease, called Personalized Parkinson Project (PPP). The study collects various forms of biomedical data of study participants, including data from wearable devices with multiple sensors. The participants are all from the Netherlands, but the data will be usable by research groups worldwide on the basis of a suitable data use agreement. The data are pseudonymised, as required by Europe’s General Data Protection Regulation (GDPR). The form of pseudonymisation that is used in this Parkinson project is based on cryptographic techniques and is ‘polymorphic’: it gives each participating research group its own ‘local’ pseudonyms. Still, the system is globally consistent, in the sense that if one research group adds data to PPP under its own local pseudonyms, the data become available for other groups under their pseudonyms. The paper gives an overview how this works, without going into the cryptographic details.

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Open-source data management system for Parkinson’s disease follow-up

PeerJ Computer Science ◽

10.7717/peerj-cs.396 ◽

2021 ◽

Vol 7 ◽

pp. e396

Author(s):

João Paulo Folador ◽

Marcus Fraga Vieira ◽

Adriano Alves Pereira ◽

Adriano de Oliveira Andrade

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Open Source ◽

Integrated System ◽

Data Management System ◽

World Population ◽

Biomedical Data ◽

System Usability Scale ◽

System Usability

Background Parkinson’s disease (PD) is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunctions. The disease affects 1% of the world population over 60 years and remains cureless. Knowledge and monitoring of PD are essential to provide better living conditions for patients. Thus, diagnostic exams and monitoring of the disease can generate a large amount of data from a given patient. This study proposes the development and usability evaluation of an integrated system, which can be used in clinical and research settings to manage biomedical data collected from PD patients. Methods A system, so-called Sistema Integrado de Dados Biomédicos (SIDABI) (Integrated Biomedical Data System), was designed following the model-view-controller (MVC) standard. A modularized architecture was created in which all the other modules are connected to a central security module. Thirty-six examiners evaluated the system usability through the System Usability Scale (SUS). The agreement between examiners was measured by Kendall’s coefficient with a significance level of 1%. Results The free and open-source web-based system was implemented using modularized and responsive methods to adapt the system features on multiple platforms. The mean SUS score was 82.99 ± 13.97 points. The overall agreement was 70.2%, as measured by Kendall’s coefficient (p < 0.001). Conclusion According to the SUS scores, the developed system has good usability. The system proposed here can help researchers to organize and share information, avoiding data loss and fragmentation. Furthermore, it can help in the follow-up of PD patients, in the training of professionals involved in the treatment of the disorder, and in studies that aim to find hidden correlations in data.

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Visualizing correlations among Parkinson biomedical data through information retrieval and machine learning techniques

Multimedia Tools and Applications ◽

10.1007/s11042-021-10506-x ◽

2021 ◽

Author(s):

Maria Frasca ◽

Genoveffa Tortora

Keyword(s):

Machine Learning ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Information Retrieval ◽

Semantic Analysis ◽

Clustering Algorithms ◽

Machine Learning Techniques ◽

Biomedical Data ◽

Learning Techniques ◽

Medical Reports

AbstractIn the last few years, the integration of researches in Computer Science and medical fields has made available to the scientific community an enormous amount of data, stored in databases. In this paper, we analyze the data available in the Parkinson’s Progression Markers Initiative (PPMI), a comprehensive observational, multi-center study designed to identify progression biomarkers important for better treatments for Parkinson’s disease. The data of PPMI participants are collected through a comprehensive battery of tests and assessments including Magnetic Resonance Imaging and DATscan imaging, collection of blood, cerebral spinal fluid, and urine samples, as well as cognitive and motor evaluations. To this aim, we propose a technique to identify a correlation between the biomedical data in the PPMI dataset for verifying the consistency of medical reports formulated during the visits and allow to correctly categorize the various patients. To correlate the information of each patient’s medical report, Information Retrieval and Machine Learning techniques have been adopted, including the Latent Semantic Analysis, Text2Vec and Doc2Vec techniques. Then, patients are grouped and classified into affected or not by using clustering algorithms according to the similarity of medical reports. Finally, we have adopted a visualization system based on the D3 framework to visualize correlations among medical reports with an interactive chart, and to support the doctor in analyzing the chronological sequence of visits in order to diagnose Parkinson’s disease early.

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Effects of repetitive transcranial magnetic stimulation on voice and speech in Parkinson's disease

The Journal of Laryngology & Otology ◽

10.1017/s0022215106002787 ◽

2005 ◽

pp. 1

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Transcranial Magnetic Stimulation ◽

Magnetic Stimulation ◽

Repetitive Transcranial Magnetic Stimulation ◽

Voice And Speech

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Emerging Drugs and Targets for Parkinson's Disease

10.1039/9781849737357 ◽

2013 ◽

Cited By ~ 3

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease

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Evaluation of Efferent Auditory System and Hearing Quality in Parkinson's Disease: Is the Difficulty in Speech Understanding in Complex Listening Conditions Related to Neural Degeneration or Aging?

Journal of Speech Language and Hearing Research ◽

10.1044/2020_jslhr-20-00337 ◽

2020 ◽

pp. 1-9

Author(s):

Nuriye Yıldırım Gökay ◽

Bülent Gündüz ◽

Fatih Söke ◽

Recep Karamert

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Auditory System ◽

Otoacoustic Emissions ◽

Pure Tone ◽

Pure Tone Audiometry ◽

Auditory Pathway ◽

Normal Hearing ◽

System Function ◽

Distortion Product

Purpose The effects of neurological diseases on the auditory system have been a notable issue for investigators because the auditory pathway is closely associated with neural systems. The purposes of this study are to evaluate the efferent auditory system function and hearing quality in Parkinson's disease (PD) and to compare the findings with age-matched individuals without PD to present a perspective on aging. Method The study included 35 individuals with PD (mean age of 48.50 ± 8.00 years) and 35 normal-hearing peers (mean age of 49 ± 10 years). The following tests were administered for all participants: the first section of the Speech, Spatial and Qualities of Hearing Scale; pure-tone audiometry, speech audiometry, tympanometry, and acoustic reflexes; and distortion product otoacoustic emissions (DPOAEs) and contralateral suppression of DPOAEs. SPSS Version 25 was used for statistical analyses, and values of p < .05 were considered statistically significant. Results There were no statistically significant differences in the pure-tone audiometry thresholds and DPOAE responses between the individuals with PD and their normal-hearing peers ( p = .732). However, statistically significant differences were found between the groups in suppression levels of DPOAEs and hearing quality ( p < .05). In addition, a statistically significant and positive correlation was found between the amount of suppression at some frequencies and the Speech, Spatial and Qualities of Hearing Scale scores. Conclusions This study indicates that medial olivocochlear efferent system function and the hearing quality of individuals with PD were affected adversely due to the results of PD pathophysiology on the hearing system. For optimal intervention and follow-up, tasks related to hearing quality in daily life can also be added to therapies for PD.

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