568 citations · 733 across the 23 of their papers we have counts for
23 papers
Feature Quality and Adaptability of Medical Foundation Models: A Comparative Evaluation for Radiographic Classification and Segmentation
Frank Li, Theo Dapamede, Mohammadreza Chavoshi +12
Foundation models (FMs) promise to generalize medical imaging, but their effectiveness varies. It remains unclear how pre-training domain (medical vs. general), paradigm (e.g., tex…
Evaluating Vision Language Models (VLMs) for Radiology: A Comprehensive Analysis
Frank Li, Hari Trivedi, Bardia Khosravi +8
Foundation models, trained on vast amounts of data using self-supervised techniques, have emerged as a promising frontier for advancing artificial intelligence (AI) applications in…
DengueNet: Dengue Prediction using Spatiotemporal Satellite Imagery for Resource-Limited Countries
Kuan-Ting Kuo, Dana Moukheiber, Sebastian Cajas Ordonez +9
Dengue fever presents a substantial challenge in developing countries where sanitation infrastructure is inadequate. The absence of comprehensive healthcare systems exacerbates the…
Healthcare Security Breaches in the United States: Insights and their Socio-Technical Implications
Megha M. Moncy, Sadia Afreen, Saptarshi Purkayastha
This research examines the pivotal role of human behavior in the realm of healthcare data management, situated at the confluence of technological advancements and human conduct. An…
Evaluation of accessibility of open-source EHRs for visually impaired users
Megha M. Moncy, Manya Pilli, Manasi Somasundaram +2
This study investigates the accessibility of open-source electronic health record (EHR) systems for individuals who are visually impaired or blind. Ensuring the accessibility of EH…
Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research
Bardia Khosravi, Frank Li, Theo Dapamede +8
Chest X-rays (CXR) are essential for diagnosing a variety of conditions, but when used on new populations, model generalizability issues limit their efficacy. Generative AI, partic…
A general-purpose AI assistant embedded in an open-source radiology information system
Saptarshi Purkayastha, Rohan Isaac, Sharon Anthony +4
Radiology AI models have made significant progress in near-human performance or surpassing it. However, AI model's partnership with human radiologist remains an unexplored challeng…
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited triplets
Ananth Reddy Bhimireddy, John Lee Burns, Saptarshi Purkayastha +1
Deep learning approaches applied to medical imaging have reached near-human or better-than-human performance on many diagnostic tasks. For instance, the CheXpert competition on det…
OSCARS: An Outlier-Sensitive Content-Based Radiography Retrieval System
Xiaoyuan Guo, Jiali Duan, Saptarshi Purkayastha +3
Improving the retrieval relevance on noisy datasets is an emerging need for the curation of a large-scale clean dataset in the medical domain. While existing methods can be applied…
MedShift: identifying shift data for medical dataset curation
Xiaoyuan Guo, Judy Wawira Gichoya, Hari Trivedi +2
To curate a high-quality dataset, identifying data variance between the internal and external sources is a fundamental and crucial step. However, methods to detect shift or varianc…
CVAD: A generic medical anomaly detector based on Cascade VAE
Xiaoyuan Guo, Judy Wawira Gichoya, Saptarshi Purkayastha +1
Detecting out-of-distribution (OOD) samples in medical imaging plays an important role for downstream medical diagnosis. However, existing OOD detectors are demonstrated on natural…
Margin-Aware Intra-Class Novelty Identification for Medical Images
Xiaoyuan Guo, Judy Wawira Gichoya, Saptarshi Purkayastha +1
Traditional anomaly detection methods focus on detecting inter-class variations while medical image novelty identification is inherently an intra-class detection problem. For examp…
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns +20
Background: In medical imaging, prior studies have demonstrated disparate AI performance by race, yet there is no known correlation for race on medical imaging that would be obviou…
Human Activity Recognition using Deep Learning Models on Smartphones and Smartwatches Sensor Data
Bolu Oluwalade, Sunil Neela, Judy Wawira +2
In recent years, human activity recognition has garnered considerable attention both in industrial and academic research because of the wide deployment of sensors, such as accelero…
Usability and Security of Different Authentication Methods for an Electronic Health Records System
Saptarshi Purkayastha, Shreya Goyal, Bolu Oluwalade +3
We conducted a survey of 67 graduate students enrolled in the Privacy and Security in Healthcare course at Indiana University Purdue University Indianapolis. This was done to measu…
Enabling Secure and Effective Biomedical Data Sharing through Cyberinfrastructure Gateways
Shreya Goyal, Saptarshi Purkayastha, Tyler Phillips +2
Dynaswap project reports on developing a coherently integrated and trustworthy holistic secure workflow protection architecture for cyberinfrastructures which can be used on virtua…
Was there COVID-19 back in 2012? Challenge for AI in Diagnosis with Similar Indications
Imon Banerjee, Priyanshu Sinha, Saptarshi Purkayastha +5
Purpose: Since the recent COVID-19 outbreak, there has been an avalanche of research papers applying deep learning based image processing to chest radiographs for detection of the…
Artificial Intelligence for Global Health: Learning From a Decade of Digital Transformation in Health Care
Varoon Mathur, Saptarshi Purkayastha, Judy Wawira Gichoya
The health needs of those living in resource-limited settings are a vastly overlooked and understudied area in the intersection of machine learning (ML) and health care. While the…
A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology Images
Pradeeban Kathiravelu, Puneet Sharma, Ashish Sharma +7
Executing machine learning (ML) pipelines in real-time on radiology images is hard due to the limited computing resources in clinical environments and the lack of efficient data tr…
Multi-label natural language processing to identify diagnosis and procedure codes from MIMIC-III inpatient notes
A. K. Bhavani Singh, Mounika Guntu, Ananth Reddy Bhimireddy +2
In the United States, 25% or greater than 200 billion dollars of hospital spending accounts for administrative costs that involve services for medical coding and billing. With the…
Natural language processing of MIMIC-III clinical notes for identifying diagnosis and procedures with neural networks
Siddhartha Nuthakki, Sunil Neela, Judy W. Gichoya +1
Coding diagnosis and procedures in medical records is a crucial process in the healthcare industry, which includes the creation of accurate billings, receiving reimbursements from…
Development and Implementation of a Dashboard for Diabetes Care Management in OpenMRS
Bhanu Teja Yandrapalli, Josette Jones, Saptarshi Purkayastha
A clinical dashboard for a patient's diabetes condition helps physicians to make better decisions based on readily available information. OpenMRS is a widely used open-source elect…
Phronesis of AI in radiology: Superhuman meets natural stupidity
Judy W. Gichoya, Siddhartha Nuthakki, Pallavi G. Maity +1
Advances in AI in the last decade have clearly made economists, politicians, journalists, and citizenry in general believe that the machines are coming to take human jobs. We revie…