Publications by authors named "Padukode R Krishnan"
Article Synopsis
- Parkinson's disease (PD) is serious and costly to treat, and recent advancements in machine learning (ML) can predict cardiovascular and stroke risks in PD patients, but challenges arise due to COVID-19's impact on these models.
- The study explores the hypothesis that COVID-19 exacerbates heart and brain damage in PD patients and proposes a deep learning (DL) model that factors in COVID-19 lung damage, alongside various medical data, for better risk stratification.
- Validation of the DL model demonstrated its effectiveness in stratifying cardiovascular/stroke risk in PD patients during the pandemic, while also addressing potential biases in artificial intelligence applications for early detection of these risks.
Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review.
Smiksha Munjral Mahesh Maindarkar Puneet Ahluwalia Anudeep Puvvula Ankush Jamthikar Padukode R Krishnan
Diagnostics (Basel)
May 2022
Article Synopsis
- * Timely detection of CVD complications in DR patients is essential, and since traditional CAD risk assessments can be costly, low-cost imaging methods like carotid B-mode ultrasound can be utilized for better risk stratification.
- * The use of artificial intelligence (AI) in analyzing large data sets helps identify risk factors for atherosclerosis in DR patients, thus aiding in CVD risk assessment and highlighting the interconnection between DR, CAD, and their implications during the COVID-19 pandemic.
Parkinson’s disease (PD) is a severe, incurable, and costly condition leading to heart failure. The link between PD and cardiovascular disease (CVD) is not available, leading to controversies and poor prognosis. Artificial Intelligence (AI) has already shown promise for CVD/stroke risk stratification.
View Article and Find Full Text PDFUnlabelled: Background and Motivation: Diagnosis of Parkinson's disease (PD) is often based on medical attention and clinical signs. It is subjective and does not have a good prognosis. Artificial Intelligence (AI) has played a promising role in the diagnosis of PD.
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