Review on AI-Based Diagnosis of Parkinson's Disorders

Review on AI-Based Diagnosis of Parkinson's Disorders

Avni Kuba, Brijanshi Rastogi, Anushree Sah, Saurabh Rawat
Copyright: © 2023 |Pages: 11
DOI: 10.4018/979-8-3693-0876-9.ch014
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Abstract

Parkinson's disease is a neurological condition that progressively damages both the motor and non-motor portions of the brain. It's crucial to remember that Parkinson's disease (PD) still has no treatment, despite the fact that medical science has advanced quickly over time.With the aid of machine learning techniques, this work aims to give a detailed analysis of the use of artificial intelligence in kinematic analysis of PD. The search included articles discussing the application of ML algorithms for Parkinson Disease diagnosis and assessment utilizing data representing mobility in the upper and lower extremities. This work is based on a number of publicly available papers. There is a thorough discussion of the available datasets and their varied features. A complete overview of the current algorithms, methods, and approaches that make use of various datasets is also offered, along with information on how they have affected the development of newer research directions. Early diagnosis and supporting rehabilitation are the most important advantages.
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2. Ai In Medicine Sector

The practice of medicine could be profoundly changed by artificial intelligence, which would be advantageous for both patients and practitioners. If AI's potential is realized, healthcare could become more precise, efficient, and available for patients everywhere (Ammour et al., 2020). Before seeing a doctor, a patient might examine a computer, bringing in “standard” medical practices sooner than we might have thought. The days of misdiagnosis and treating disease symptoms rather than their underlying causes may be a thing of the past thanks to breakthroughs in artificial intelligence (Pereira et al., 2019).

Think about the amount of room that would need to be made available on your laptop in order to contain a complete 3D model of an organ or the number of years' worth of blood pressure records you possess. The expanding body of data generated in clinics and maintained in electronic medical records through routine testing and medical imaging enables additional uses of artificial intelligence and highly efficient data-driven treatment. These applications have changed and will continue to alter the approaches taken by doctors and researchers to deal with clinical issues (Khang & Rana et al., 2023).

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