Cardiovascular/Stroke Risk Stratification in Parkinson’s Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review

Suri, Jasjit S.; Sauseng, Paul; Maindarkar, Mahesh; Puvvula, Anudeep; Saxena, Sanjay; Saba, Luca; Turk, Monika; Laird, John R.; Khanna, Narendra N.; Višković, Klaudija; Singh, Inder; Kalra, Mannudeep M.; Krishnan, Padukode R.; Johri, Amer M.; Paraskevas, Kosmas I.

doi:10.3390/metabo12040312

Cited by 31 publications

(18 citation statements)

References 220 publications

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“…Cardiovascular disease (CVD) is a lifestyle-related disease (LSRD) caused by the dysfunction and cell death of cardiomyocytes via ischemic or non-ischemic events [ 1 , 2 , 3 ]. Cardiac fibroblasts are crucial for the repair and remodeling of the heart.…”

Section: Introductionmentioning

confidence: 99%

Intracellular Toxic Advanced Glycation End-Products May Induce Cell Death and Suppress Cardiac Fibroblasts

2022

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Cardiovascular disease (CVD) is a lifestyle-related disease (LSRD) induced by the dysfunction and cell death of cardiomyocytes. Cardiac fibroblasts are activated and differentiate in response to specific signals, such as transforming growth factor-β released from injured cardiomyocytes, and are crucial for the protection of cardiomyocytes, cardiac tissue repair, and remodeling. In contrast, cardiac fibroblasts have been shown to induce injury or death of cardiomyocytes and are implicated in the pathogenesis of diseases such as cardiac hypertrophy. We designated glyceraldehyde-derived advanced glycation end-products (AGEs) as toxic AGEs (TAGE) due to their cytotoxicity and association with LSRD. Intracellular TAGE in cardiomyocytes decreased their beating rate and induced cell death in the absence of myocardial ischemia. The TAGE levels in blood were elevated in patients with CVD and were associated with myocardial ischemia along with increased risk of atherosclerosis in vascular endothelial cells in vitro. The relationships between the dysfunction or cell death of cardiac fibroblasts and intracellular and extracellular TAGE, which are secreted from certain organs, remain unclear. We examined the cytotoxicity of intracellular TAGE by a slot blot analysis, and TAGE-modified bovine serum albumin (TAGE-BSA), a model of extracellular TAGE, in normal human cardiac fibroblasts (HCF). Intracellular TAGE induced cell death in normal HCF, whereas TAGE-BSA did not, even at aberrantly high non-physiological levels. Therefore, only intracellular TAGE induced cell death in HCF under physiological conditions, possibly inhibiting the role of HCF.

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Section: Introductionmentioning

confidence: 99%

Intracellular Toxic Advanced Glycation End-Products May Induce Cell Death and Suppress Cardiac Fibroblasts

2022

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“…AI contains various combinations of technologies. The vast majority of these technologies have an immediate application in the field of medicine, even though the specific procedures and tasks with which they can help vary considerably [ 14 , 89 , 90 , 91 , 92 ]. The following list identifies and provides explanations for several essential AI technologies for the healthcare industry.…”

Section: An Overview Of Artificial Intelligence Applications In Healt...mentioning

confidence: 99%

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

Khanna¹,

Maindarkar

Viswanathan

et al. 2022

Healthcare

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Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals.

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“…This CUSIP is then used as a covariate in the ML algorithm to further improve the results ( Figure 16 ) [ 246 ]. Suri et al [ 248 ] explained the risk of CVD/stroke in PD patients by using carotid artery imaging, since it was low-cost, non-invasive imaging for the screening. PD patients will benefit from the adoption of this low-cost B-mode ultrasonography since it will allow for the characterization of plaque tissue.…”

Section: Deep Learning For Cvd/stroke Risk Assessment In Pd Patients ...mentioning

confidence: 99%

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID-19: A Narrative Review

Suri¹,

Maindarkar

Sauseng

et al. 2022

Diagnostics

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Background and Motivation: Parkinson’s disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients. The presence of COVID-19 causes the ML systems to become severely non-linear and poses challenges in cardiovascular/stroke risk stratification. Further, due to comorbidity, sample size constraints, and poor scientific and clinical validation techniques, there have been no well-explained ML paradigms. Deep neural networks are powerful learning machines that generalize non-linear conditions. This study presents a novel investigation of deep learning (DL) solutions for CVD/stroke risk prediction in PD patients affected by the COVID-19 framework. Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID-19 framework. We study the hypothesis that PD in the presence of COVID-19 can cause more harm to the heart and brain than in non-COVID-19 conditions. COVID-19 lung damage severity can be used as a covariate during DL training model designs. We, therefore, propose a DL model for the estimation of, (i) COVID-19 lesions in computed tomography (CT) scans and (ii) combining the covariates of PD, COVID-19 lesions, office and laboratory arterial atherosclerotic image-based biomarkers, and medicine usage for the PD patients for the design of DL point-based models for CVD/stroke risk stratification. Results: We validated the feasibility of CVD/stroke risk stratification in PD patients in the presence of a COVID-19 environment and this was also verified. DL architectures like long short-term memory (LSTM), and recurrent neural network (RNN) were studied for CVD/stroke risk stratification showing powerful designs. Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID-19.Conclusion: The DL is a very powerful tool for predicting CVD/stroke risk in PD patients affected by COVID-19.

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Cardiovascular/Stroke Risk Stratification in Parkinson’s Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review

Cited by 31 publications

References 220 publications

Intracellular Toxic Advanced Glycation End-Products May Induce Cell Death and Suppress Cardiac Fibroblasts

Intracellular Toxic Advanced Glycation End-Products May Induce Cell Death and Suppress Cardiac Fibroblasts

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID-19: A Narrative Review

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