Imperative Role of Machine Learning Algorithm for Detection of Parkinson’s Disease: Review, Challenges and Recommendations

Rana, Arti; Dumka, Ankur; Singh, Rajesh; Panda, Manoj Kumar; Priyadarshi, Neeraj; Twala, Bhekisipho

doi:10.3390/diagnostics12082003

Cited by 57 publications

(23 citation statements)

References 108 publications

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“…Its applications found their way into clinical routine, significantly improving patient care [ 21 , 23 ]. Multiple studies have explored the potential use of artificial intelligence in many areas of medicine, such as cardiology [ 21 ], neurology [ 20 ], oncology [ 22 ], haematology [ 42 ], nephrology [ 43 ], gastroenterology, hepatology, orthopaedics and rheumatology [ 21 ]. The findings hold great promise for revolutionising clinical care, not only in terms of better diagnostic and therapeutic options for patients but also by facilitating decision-making and reducing cognitive load for clinicians.…”

Section: Discussionmentioning

confidence: 99%

“…It is, therefore, necessary to consider how clinicians working with this technology can be supported. One of the solutions for significantly improving patient care is the application of artificial intelligence and machine learning [ 20 , 21 , 22 , 23 ]. Situation awareness and user-centred design principles also play an essential role in facilitating decision-making in complex clinical situations [ 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

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User Perceptions of ROTEM-Guided Haemostatic Resuscitation: A Mixed Qualitative–Quantitative Study

et al. 2023

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Viscoelastic point-of-care haemostatic resuscitation methods, such as ROTEM or TEG, are crucial in deciding on time-efficient personalised coagulation interventions. International transfusion guidelines emphasise increased patient safety and reduced treatment costs. We analysed care providers’ perceptions of ROTEM to identify perceived strengths and areas for improvement. We conducted a single-centre, mixed qualitative–quantitative study consisting of interviews followed by an online survey. Using a template approach, we first identified themes in the responses given by care providers about ROTEM. Later, the participants rated six statements based on the identified themes on five-point Likert scales in an online questionnaire. Seventy-seven participants were interviewed, and 52 completed the online survey. By analysing user perceptions, we identified ten themes. The most common positive theme was “high accuracy”. The most common negative theme was “need for training”. In the online survey, 94% of participants agreed that monitoring the real-time ROTEM temograms helps to initiate targeted treatment more quickly and 81% agreed that recurrent ROTEM training would be beneficial. Anaesthesia care providers found ROTEM to be accurate and quickly available to support decision-making in dynamic and complex haemostatic situations. However, clinicians identified that interpreting ROTEM is a complex and cognitively demanding task that requires significant training needs.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

User Perceptions of ROTEM-Guided Haemostatic Resuscitation: A Mixed Qualitative–Quantitative Study

et al. 2023

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“…PD, a degenerative disease of the central nervous system with a low mortality and high disability rate, brings great inconvenience to patients' lives, seriously threatens the physical and mental health of the elderly population, and places a burden on society. This has become a public health problem that needs to be solved urgently (Rana et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Effects of aquatic exercise on the improvement of lower-extremity motor function and quality of life in patients with Parkinson’s disease: A meta-analysis

Dai

Yuan²,

Wang³

et al. 2023

Front. Physiol.

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Objective: To systematically evaluate the effect of aquatic exercise interventions on the improvement of lower-extremity motor function and quality of life in patients with Parkinson’s disease.Methods: Two researchers independently searched the literature using the PubMed, Web of Science, Embase, and Cochrane Library databases. The search period was from the establishment of the database to December 2021. The subject heading search included “hydrotherapy,” “hydro therapies,” “hydro therapeutics,” “water therapy,” “aquatic exercise therapy,” “aquatic therapy,” “water-based exercise,” “Parkinson,” “Parkinson disease,” “Parkinson’s disease,” “Parkinson’s syndrome,” “primary Parkinsonism,” “paralysis agitans,” and “randomized controlled trial (RCT).”Result: A total of 698 articles were retrieved from the four databases by searching for subject headings, and 10 RCT articles were finally included. The balance ability of aquatic exercise in patients with Parkinson’s disease (weighted mean differences [WMD] = 2.234, 95% CI: 1.112–3.357, Z = 3.9, p < 0.01), walking ability (WMD = −0.911, 95% CI: −1.581 to −0.241, Z = 2.67, p < 0.01), and quality of life (WMD = −5.057, 95% CI: −9.610 to −0.504, Z = 2.18, p = 0.029) were improved, but there was no significant difference in motor function (WMD = −0.328, 95% CI: −1.781 to 1.125, Z = 0.44, p = 0.658).Conclusion: Compared with conventional rehabilitation therapy, aquatic exercise can effectively improve balance, walking ability, and quality of life in patients with Parkinson’s disease. However, it had no obvious effect on improving motor function. This study was limited by the number and quality of the included studies, and more high-quality studies are needed to verify this.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42022365103.

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“…The challenge in detecting symptoms of such nervous system disorders through a computerised practice is accomplished via several modalities (such as speech, handwriting, radiology, gait, etc.) which are employed to reveal indicators of discriminant symptoms associated with neurodegenerative disorders, see [ 3 , 4 ]. The idea is to map different modality-derived features to the various symptoms and obtain discriminant information about the studied illness.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the same symptoms manifest in multiple of these conditions [1], demanding expensive equipment and advanced expertise for the correct diagnosis. As a solution, the developments of artificial intelligence in biotechnology have started to support these medical settings with automated computational tools that can increasingly identify disorders' abnormalities in real-life-sensing environments [2][3][4][5]. The challenge in detecting symptoms of such nervous system disorders through a computerised practice is accomplished via several modalities (such as speech, handwriting, radiology, gait, etc.)…”

Section: Introductionmentioning

confidence: 99%

Ataxic speech disorders and Parkinson’s disease diagnostics via stochastic embedding of empirical mode decomposition

2023

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Medical diagnostic methods that utilise modalities of patient symptoms such as speech are increasingly being used for initial diagnostic purposes and monitoring disease state progression. Speech disorders are particularly prevalent in neurological degenerative diseases such as Parkinson’s disease, the focus of the study undertaken in this work. We will demonstrate state-of-the-art statistical time-series methods that combine elements of statistical time series modelling and signal processing with modern machine learning methods based on Gaussian process models to develop methods to accurately detect a core symptom of speech disorder in individuals who have Parkinson’s disease. We will show that the proposed methods out-perform standard best practices of speech diagnostics in detecting ataxic speech disorders, and we will focus the study, particularly on a detailed analysis of a well regarded Parkinson’s data speech study publicly available making all our results reproducible. The methodology developed is based on a specialised technique not widely adopted in medical statistics that found great success in other domains such as signal processing, seismology, speech analysis and ecology. In this work, we will present this method from a statistical perspective and generalise it to a stochastic model, which will be used to design a test for speech disorders when applied to speech time series signals. As such, this work is making contributions both of a practical and statistical methodological nature.

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Imperative Role of Machine Learning Algorithm for Detection of Parkinson’s Disease: Review, Challenges and Recommendations

Cited by 57 publications

References 108 publications

User Perceptions of ROTEM-Guided Haemostatic Resuscitation: A Mixed Qualitative–Quantitative Study

User Perceptions of ROTEM-Guided Haemostatic Resuscitation: A Mixed Qualitative–Quantitative Study

Effects of aquatic exercise on the improvement of lower-extremity motor function and quality of life in patients with Parkinson’s disease: A meta-analysis

Ataxic speech disorders and Parkinson’s disease diagnostics via stochastic embedding of empirical mode decomposition

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