Parkinson’s disease is the second most frequent neurodegenerative disorder, affecting about 1% of adults over 60 worldwide. Other movement disorders like Multiple System Atrophy, Huntington’s Disease, Dystonia, or cerebellar ataxias may be less common but severely impair patients’ life quality. Not only is the pathophysiology of many of these diseases incompletely understood, but diagnostic tools and therapeutic interventions are often insufficient as well. Artificial Intelligence (AI) can be defined as computer-based intelligence able to perform typically human-like tasks. Machine learning (ML) is a central feature of AI. The applications of AI and ML within the healthcare settings are fresh, exciting, and innovative. They might be engaged in developing and applying new methods for disease diagnosis and treatment, the drug discovery process, and delving into the pathophysiology of some conditions.
The prevalence of Parkinson’s and other abnormal movement diseases’ imparts a considerable burden in healthcare. Their genesis and contributing factors are not entirely understood. We aim to collect scientific articles that use AI/ML-based tools to dig deeper into the molecular and biological mechanisms causing these diseases. Studies using these tools to better understand the genetics underlying these diseasesare welcome. Also, those using AI/ML technology for Parkinson’s disease and other movement disorders diagnosis, prognosis, and treatment, including developing new therapeutic interventions.
We will consider original articles, short communications, non-systematic and systematic reviews, and metanalysis for inclusion in this Research Topic. Studies can use in vivo, ex vivo, in vitro, or in silico models. Technical reports will only be considered, provided they are included in the scientific experimental procedure. Papers should address the use of AI or ML in one of the following topics:
- New cellular or molecular disease mechanisms’ exploration or identification
- Impact of genetic mutations on disease development and characteristics
- Basic, clinical, or translational aspects in new drug discovery
- New diagnostic procedures
- New prognostic or risk factors
Parkinson’s disease is the second most frequent neurodegenerative disorder, affecting about 1% of adults over 60 worldwide. Other movement disorders like Multiple System Atrophy, Huntington’s Disease, Dystonia, or cerebellar ataxias may be less common but severely impair patients’ life quality. Not only is the pathophysiology of many of these diseases incompletely understood, but diagnostic tools and therapeutic interventions are often insufficient as well. Artificial Intelligence (AI) can be defined as computer-based intelligence able to perform typically human-like tasks. Machine learning (ML) is a central feature of AI. The applications of AI and ML within the healthcare settings are fresh, exciting, and innovative. They might be engaged in developing and applying new methods for disease diagnosis and treatment, the drug discovery process, and delving into the pathophysiology of some conditions.
The prevalence of Parkinson’s and other abnormal movement diseases’ imparts a considerable burden in healthcare. Their genesis and contributing factors are not entirely understood. We aim to collect scientific articles that use AI/ML-based tools to dig deeper into the molecular and biological mechanisms causing these diseases. Studies using these tools to better understand the genetics underlying these diseasesare welcome. Also, those using AI/ML technology for Parkinson’s disease and other movement disorders diagnosis, prognosis, and treatment, including developing new therapeutic interventions.
We will consider original articles, short communications, non-systematic and systematic reviews, and metanalysis for inclusion in this Research Topic. Studies can use in vivo, ex vivo, in vitro, or in silico models. Technical reports will only be considered, provided they are included in the scientific experimental procedure. Papers should address the use of AI or ML in one of the following topics:
- New cellular or molecular disease mechanisms’ exploration or identification
- Impact of genetic mutations on disease development and characteristics
- Basic, clinical, or translational aspects in new drug discovery
- New diagnostic procedures
- New prognostic or risk factors