Anusua Trivedi
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View article: Reinforcement Learning for Optimizing RAG for Domain Chatbots
Reinforcement Learning for Optimizing RAG for Domain Chatbots Open
With the advent of Large Language Models (LLM), conversational assistants have become prevalent for domain use cases. LLMs acquire the ability to contextual question answering through training, and Retrieval Augmented Generation (RAG) furt…
View article: Maternal infections in pregnancy and the risk of sudden unexpected infant death in the offspring in the U.S., 2011–2015
Maternal infections in pregnancy and the risk of sudden unexpected infant death in the offspring in the U.S., 2011–2015 Open
Background Infection is thought to play a part in some infant deaths. Maternal infection in pregnancy has focused on chlamydia with some reports suggesting an association with sudden unexpected infant death (SUID). Objectives We hypothesiz…
View article: Label efficient semi-supervised conversational intent classification
Label efficient semi-supervised conversational intent classification Open
To provide a convenient shopping experience and to answer user queries at scale, conversational platforms are essential for e-commerce. The user queries can be pre-purchase questions, such as product specifications and delivery time relate…
View article: Domain-specific transformer models for query translation
Domain-specific transformer models for query translation Open
Due to the democratization of e-commerce, many product companies are listing their goods for online shopping. For periodic buying within a domain such as Grocery, consumers are generally inclined to buy certain brands of products.Due to a …
View article: Machine learning-based derivation and external validation of a tool to predict death and development of organ failure in hospitalized patients with COVID-19
Machine learning-based derivation and external validation of a tool to predict death and development of organ failure in hospitalized patients with COVID-19 Open
COVID-19 mortality risk stratification tools could improve care, inform accurate and rapid triage decisions, and guide family discussions regarding goals of care. A minority of COVID-19 prognostic tools have been tested in external cohorts…
View article: Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement Open
In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing dataset…
View article: Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes
Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes Open
The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelli…
View article: Answerability: A custom metric for evaluating chatbot performance
Answerability: A custom metric for evaluating chatbot performance Open
Pranav Gupta, Anand A. Rajasekar, Amisha Patel, Mandar Kulkarni, Alexander Sunell, Kyung Kim, Krishnan Ganapathy, Anusua Trivedi. Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM). 2022.
View article: Parameters of Chronic Kidney Disease to Identify Outpatients at Increased Risk for COVID-19 Mortality: A Cohort Study of UK Biobank Participants
Parameters of Chronic Kidney Disease to Identify Outpatients at Increased Risk for COVID-19 Mortality: A Cohort Study of UK Biobank Participants Open
Coronavirus Disease (COVID-19) has resulted in a pandemic affecting more than a hundred countries worldwide [1].Limited worldwide supply of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV) requires policymakers t…
View article: Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19
Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19 Open
BackgroundCOVID-19 mortality risk stratification tools could improve care, inform accurate and rapid triage decisions, and guide family discussions regarding goals of care. A minority of COVID-19 prognostic tools have been tested in extern…
View article: Retinal Microvasculature as Biomarker for Diabetes and Cardiovascular Diseases
Retinal Microvasculature as Biomarker for Diabetes and Cardiovascular Diseases Open
Purpose: To demonstrate that retinal microvasculature per se is a reliable biomarker for Diabetic Retinopathy (DR) and, by extension, cardiovascular diseases. Methods: Deep Learning Convolutional Neural Networks (CNN) applied to color fund…
View article: Becoming Good at AI for Good
Becoming Good at AI for Good Open
AI for good (AI4G) projects involve developing and applying artificial intelligence (AI) based solutions to further goals in areas such as sustainability, health, humanitarian aid, and social justice. Developing and deploying such solution…
View article: Defending Democracy: Using Deep Learning to Identify and Prevent Misinformation
Defending Democracy: Using Deep Learning to Identify and Prevent Misinformation Open
The rise in online misinformation in recent years threatens democracies by distorting authentic public discourse and causing confusion, fear, and even, in extreme cases, violence. There is a need to understand the spread of false content t…
View article: Height Estimation of Children under Five Years using Depth Images
Height Estimation of Children under Five Years using Depth Images Open
Malnutrition is a global health crisis and is the leading cause of death among children under five. Detecting malnutrition requires anthropometric measurements of weight, height, and middle-upper arm circumference. However, measuring them …
View article: privGAN: Protecting GANs from membership inference attacks at low cost to utility
privGAN: Protecting GANs from membership inference attacks at low cost to utility Open
Generative Adversarial Networks (GANs) have made releasing of synthetic images a viable approach to share data without releasing the original dataset. It has been shown that such synthetic data can be used for a variety of downstream tasks…
View article: Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement Open
In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing dataset…
View article: Effective Deep Learning Approaches for Predicting COVID-19 Outcomes from Chest Computed Tomography Volumes
Effective Deep Learning Approaches for Predicting COVID-19 Outcomes from Chest Computed Tomography Volumes Open
The rapid evolution of the novel coronavirus SARS-CoV-2 pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence ap…
View article: Improving Lesion Detection by exploring bias on Skin Lesion dataset
Improving Lesion Detection by exploring bias on Skin Lesion dataset Open
All datasets contain some biases, often unintentional, due to how they were acquired and annotated. These biases distort machine-learning models' performance, creating spurious correlations that the models can unfairly exploit, or, contrar…
View article: Protecting GANs against privacy attacks by preventing overfitting.
Protecting GANs against privacy attacks by preventing overfitting. Open
Generative Adversarial Networks (GANs) have made releasing of synthetic images a viable approach to share data without releasing the original dataset. It has been shown that such synthetic data can be used for a variety of downstream tasks…
View article: privGAN: Protecting GANs from membership inference attacks at low cost
privGAN: Protecting GANs from membership inference attacks at low cost Open
Generative Adversarial Networks (GANs) have made releasing of synthetic images a viable approach to share data without releasing the original dataset. It has been shown that such synthetic data can be used for a variety of downstream tasks…
View article: Risks of Using Non-verified Open Data: A case study on using Machine Learning techniques for predicting Pregnancy Outcomes in India
Risks of Using Non-verified Open Data: A case study on using Machine Learning techniques for predicting Pregnancy Outcomes in India Open
Artificial intelligence (AI) has evolved considerably in the last few years. While applications of AI is now becoming more common in fields like retail and marketing, application of AI in solving problems related to developing countries is…