Bhavana Baraskar

Dr. Bhavana Baraskar

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Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 May 2025 in Sensors
Verified
Journal Article
Open access
PDF file
PMPratyusha Muddaloor
Pratyusha Muddaloor
BBBhavana Baraskar
Bhavana Baraskar
HSHriday Ronak Shah
Hriday Ronak Shah
KGKeerthy Gopalakrishnan Gopalakrishnan
Keerthy Gopalakrishnan Gopalakrishnan
DSDivyanshi Sood
Divyanshi Sood
Shivaram P. ArunachalamShivaram P. Arunachalam
Shivaram P. Arunachalam
The human voice is an important medium of communication and expression of feelings or thoughts. Disruption in the regulatory systems of the human voice can be analyzed and used as a diagnostic tool, labeling voice as a potential “biomarker”. Conversational artificial intelligence is at the core of voice-powered technologies, enabling intelligent interactions between machines. Due to its richness and availability, voice can be leveraged for predictive analytics and enhanced healthcare insights. Utilizing this idea, we reviewed artificial intelligence (AI) models that have executed vocal analysis and their outcomes. Recordings undergo extraction of useful vocal features to be analyzed by neural networks and machine learning models. Studies reveal machine learning models to be superior to spectral analysis in dynamically combining the huge amount of data of vocal features. Clinical applications of a vocal biomarker exist in neurological diseases such as Parkinson’s, Alzheimer’s, psychological disorders, DM, CHF, CAD, aspiration, GERD, and pulmonary diseases, including COVID-19. The primary ethical challenge when incorporating voice as a diagnostic tool is that of privacy and security. To eliminate this, encryption methods exist to convert patient-identifiable vocal data into a more secure, private nature. Advancements in AI have expanded the capabilities and future potential of voice as a digital health solution.

25 July 2023 in Journal of Imaging
Verified
Journal Article
Open access
PDF file
MSMansunderbir Singh
Mansunderbir Singh
PAPriyanka Anvekar
Priyanka Anvekar
BBBhavana Baraskar
Bhavana Baraskar
NPNamratha Pallipamu
Namratha Pallipamu
SGSrikanth Gadam
Srikanth Gadam
Shivaram P. ArunachalamShivaram P. Arunachalam
Shivaram P. Arunachalam
Pancreatic carcinoma (Ca Pancreas) is the third leading cause of cancer-related deaths in the world. The malignancies of the pancreas can be diagnosed with the help of various imaging modalities. An endoscopic ultrasound with a tissue biopsy is so far considered to be the gold standard in terms of the detection of Ca Pancreas, especially for lesions <2 mm. However, other methods, like computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), are also conventionally used. Moreover, newer techniques, like proteomics, radiomics, metabolomics, and artificial intelligence (AI), are slowly being introduced for diagnosing pancreatic cancer. Regardless, it is still a challenge to diagnose pancreatic carcinoma non-invasively at an early stage due to its delayed presentation. Similarly, this also makes it difficult to demonstrate an association between Ca Pancreas and other vital organs of the body, such as the heart. A number of studies have proven a correlation between the heart and pancreatic cancer. The tumor of the pancreas affects the heart at the physiological, as well as the molecular, level. An overexpression of the SMAD4 gene; a disruption in biomolecules, such as IGF, MAPK, and ApoE; and increased CA19-9 markers are a few of the many factors that are noted to affect cardiovascular systems with pancreatic malignancies. A comprehensive review of this correlation will aid researchers in conducting studies to help establish a definite relation between the two organs and discover ways to use it for the early detection of Ca Pancreas.

28 July 2023 in Journal Of Nephrology
Verified
Journal Article
Closed access
PDF file
CPCharmy Parikh
Charmy Parikh
HUHenil Upadhyay
Henil Upadhyay
SPSuyog Patel
Suyog Patel
RSRamaswamy Sundararajan
Ramaswamy Sundararajan
DSDhairya Shah
Dhairya Shah
SGSanjeev Gupta
Sanjeev Gupta
Background: Severe acute respiratory syndrome coronavirus 2 infection has caused significant morbidity and mortality. Vaccines produced against this virus have proven highly effective. However, adverse events following vaccination have also been reported. One of them is nephrotic syndrome, that can be associated with different pathologic pictures. This review aims to provide a wider understanding of incidence, etiopathogenesis, and management of nephrotic syndrome following vaccination against SARS-CoV-2. Methods and results: A literature search was undertaken using appropriate keywords in various databases like PubMed, Google Scholar, Europe PMC, and Science Direct. Twenty-one articles were included following qualitative assessment. Data of 74 patients from these articles were included. Discussion: The pathogenesis of nephrotic syndrome following COVID vaccination has been widely attributed to the activation of angiotensin-converting enzyme-2 receptors, leading to podocyte effacement. Relapses have also been reported in patients with prior history of nephrotic syndrome following COVID-19 vaccination. A renal biopsy is necessary to identify the histopathological picture. Management of COVID-19 vaccine-induced nephrotic syndrome was mainly reported as successfully attainable with corticosteroids and supportive management. Conclusion: Further investigations will help in establishing an early diagnosis and salvaging kidney function. Graphical