Publications by authors named "Aishwarya Jadhav"

Multisystem Inflammatory Syndrome in Children (MIS-C) is a potentially life-threatening complication of COVID-19. The pathophysiological mechanisms leading to severe disease are poorly understood. This study leveraged clinical samples from a well-characterized cohort of children hospitalized with COVID-19 or MIS-C to compare immune-mediated biomarkers.

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This work presents a comprehensive approach to reduce bias in word embedding vectors and evaluate the impact on various Natural Language Processing (NLP) tasks. Two GloVe variations (840B and 50) are debiased by identifying the gender direction in the word embedding space and then removing or reducing the gender component from the embeddings of target words, while preserving useful semantic information. Their gender bias is assessed through the Word Embedding Association Test.

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Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious condition that can develop 4-6 weeks after a school age child becomes infected by SARS-CoV-2. To date, in the United States more than 8,862 cases of MIS-C have been identified and 72 deaths have occurred. This syndrome typically affects children between the ages of 5-13; 57% are Hispanic/Latino/Black/non-Hispanic, 61% of patients are males and 100% have either tested positive for SARS-CoV-2 or had direct contact with someone with COVID-19.

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Background: When the upper arm (UA) is inaccessible or a standard-sized blood pressure (BP) cuff is unavailable, some healthcare workers use the forearm (FA) to measure BP with a mercury sphygmomanometer.

Objective: The objective was to determine the accuracy of BP measurement in the arm and FA.

Design: Prospective, randomized study.

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