7 citations · 7 across the 5 of their papers we have counts for
6 papers
Investigating Trustworthiness of Nonparametric Deep Survival Models for Alzheimer's Disease Progression Analysis
Jacob Thrasher, Kaitlyn Heintzelman, Peter Martone +4
Alzheimer's Dementia (AD) is a progressive neurodegenerative disease marked by irreversible decline, making reliable modeling of its progression essential for effective patient car…
FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning
Alina Devkota, Jacob Thrasher, Donald Adjeroh +2
Federated Learning (FL) enables collaborative model training across multiple clients without sharing their private data. However, data heterogeneity across clients leads to client…
Enhancing Retinal Disease Classification from OCTA Images via Active Learning Techniques
Jacob Thrasher, Annahita Amireskandari, Prashnna Gyawali
Eye diseases are common in older Americans and can lead to decreased vision and blindness. Recent advancements in imaging technologies allow clinicians to capture high-quality imag…
TE-SSL: Time and Event-aware Self Supervised Learning for Alzheimer's Disease Progression Analysis
Jacob Thrasher, Alina Devkota, Ahmed Tafti +2
Alzheimer's Dementia (AD) represents one of the most pressing challenges in the field of neurodegenerative disorders, with its progression analysis being crucial for understanding…
Segmentation of Maya hieroglyphs through fine-tuned foundation models
FNU Shivam, Megan Leight, Mary Kate Kelly +5
The study of Maya hieroglyphic writing unlocks the rich history of cultural and societal knowledge embedded within this ancient civilization's visual narrative. Artificial Intellig…
Multimodal Federated Learning in Healthcare: a Review
Jacob Thrasher, Alina Devkota, Prasiddha Siwakotai +5
Recent advancements in multimodal machine learning have empowered the development of accurate and robust AI systems in the medical domain, especially within centralized database sy…