Search Results for author: Saptarshi Purkayastha

Found 16 papers, 6 papers with code

DengueNet: Dengue Prediction using Spatiotemporal Satellite Imagery for Resource-Limited Countries

1 code implementation20 Jan 2024 Kuan-Ting Kuo, Dana Moukheiber, Sebastian Cajas Ordonez, David Restrepo, Atika Rahman Paddo, Tsung-Yu Chen, Lama Moukheiber, Mira Moukheiber, Sulaiman Moukheiber, Saptarshi Purkayastha, Po-Chih Kuo, Leo Anthony Celi

In this study, our aim is to improve health equity in resource-constrained countries by exploring the effectiveness of high-resolution satellite imagery as a nontraditional and readily accessible data source.

Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research

1 code implementation15 Nov 2023 Bardia Khosravi, Frank Li, Theo Dapamede, Pouria Rouzrokh, Cooper U. Gamble, Hari M. Trivedi, Cody C. Wyles, Andrew B. Sellergren, Saptarshi Purkayastha, Bradley J. Erickson, Judy W. Gichoya

This study examines the impact of synthetic data supplementation, using diffusion models, on the performance of deep learning (DL) classifiers for CXR analysis.

Denoising

MedShift: identifying shift data for medical dataset curation

no code implementations27 Dec 2021 Xiaoyuan Guo, Judy Wawira Gichoya, Hari Trivedi, Saptarshi Purkayastha, Imon Banerjee

Given an internal dataset A as the base source, we first train anomaly detectors for each class of dataset A to learn internal distributions in an unsupervised way.

Margin-Aware Intra-Class Novelty Identification for Medical Images

1 code implementation31 Jul 2021 Xiaoyuan Guo, Judy Wawira Gichoya, Saptarshi Purkayastha, Imon Banerjee

Traditional anomaly detection methods focus on detecting inter-class variations while medical image novelty identification is inherently an intra-class detection problem.

Anomaly Detection Novelty Detection

Reading Race: AI Recognises Patient's Racial Identity In Medical Images

no code implementations21 Jul 2021 Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, Matthew P Lungren, Lyle Palmer, Brandon J Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W Gichoya

Methods: Using private and public datasets we evaluate: A) performance quantification of deep learning models to detect race from medical images, including the ability of these models to generalize to external environments and across multiple imaging modalities, B) assessment of possible confounding anatomic and phenotype population features, such as disease distribution and body habitus as predictors of race, and C) investigation into the underlying mechanism by which AI models can recognize race.

Human Activity Recognition using Deep Learning Models on Smartphones and Smartwatches Sensor Data

no code implementations28 Feb 2021 Bolu Oluwalade, Sunil Neela, Judy Wawira, Tobiloba Adejumo, Saptarshi Purkayastha

Additionally, the CNN model for the watch accelerometer was better able to classify non-hand oriented activities when compared to hand-oriented activities.

Human Activity Recognition

Usability and Security of Different Authentication Methods for an Electronic Health Records System

no code implementations23 Feb 2021 Saptarshi Purkayastha, Shreya Goyal, Bolu Oluwalade, Tyler Phillips, Huanmei Wu, Xukai Zou

From the PLS-SEM analysis, it was found that security has a positive impact on usability for Single sign-on and bio-capsule facial authentication methods.

Cryptography and Security

Enabling Secure and Effective Biomedical Data Sharing through Cyberinfrastructure Gateways

no code implementations23 Dec 2020 Shreya Goyal, Saptarshi Purkayastha, Tyler Phillips, Rob Quick, Alexis Britt

Dynaswap project reports on developing a coherently integrated and trustworthy holistic secure workflow protection architecture for cyberinfrastructures which can be used on virtual machines deployed through cyberinfrastructure (CI) services such as JetStream.

Cryptography and Security

A DICOM Framework for Machine Learning Pipelines against Real-Time Radiology Images

1 code implementation16 Apr 2020 Pradeeban Kathiravelu, Puneet Sharma, ASHISH SHARMA, Imon Banerjee, Hari Trivedi, Saptarshi Purkayastha, Priyanshu Sinha, Alexandre Cadrin-Chenevert, Nabile Safdar, Judy Wawira Gichoya

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 transfer capabilities to run them on research clusters.

BIG-bench Machine Learning

Multi-label natural language processing to identify diagnosis and procedure codes from MIMIC-III inpatient notes

no code implementations17 Mar 2020 A. K. Bhavani Singh, Mounika Guntu, Ananth Reddy Bhimireddy, Judy W. Gichoya, Saptarshi Purkayastha

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.

Language Modelling Multi-Label Classification

Natural language processing of MIMIC-III clinical notes for identifying diagnosis and procedures with neural networks

no code implementations28 Dec 2019 Siddhartha Nuthakki, Sunil Neela, Judy W. Gichoya, Saptarshi Purkayastha

In this paper, we report the performance of a natural language processing model that can map clinical notes to medical codes, and predict final diagnosis from unstructured entries of history of present illness, symptoms at the time of admission, etc.

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