10 citations · 14 across the 18 of their papers we have counts for
19 papers
Evaluating TabPFN for Mild Cognitive Impairment to Alzheimer's Disease Conversion in Data Limited Settings
Brad Ye, Bulent Soykan, Gulsah Hancerliogullari Koksalmis +2
Accurate prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimers Diseases (AD) is essential for early intervention, however, developing reliable conversion pred…
FMCL: Class-Aware Client Clustering with Foundation Model Representations for Heterogeneous Federated Learning
Mahad Ali, Laura J. Brattain
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, yet its performance deteriorates under statistical heterogeneity.…
Toward Personalized Digital Twins for Cognitive Decline Assessment: A Multimodal, Uncertainty-Aware Framework
Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang +1
Cognitive decline is highly heterogeneous across individuals, which complicates prognosis, trial design, and treatment planning. We present the Personalized Cognitive Decline Asses…
CognitiveTwin: Robust Multi-Modal Digital Twins for Predicting Cognitive Decline in Alzheimer's Disease
Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang +1
Predicting individual cognitive decline in Alzheimer's disease (AD) is difficult due to the heterogeneity of disease progression. Reliable clinical tools require not only high accu…
GeoVision-Enabled Digital Twin for Hybrid Autonomous-Teleoperated Medical Responses
Parham Kebria, Soheil Sabri, Laura J Brattain
Remote medical response systems are increasingly being deployed to support emergency care in disaster-affected and infrastructure-limited environments. Enabled by GeoVision capabil…
Hybrid Diffusion Model for Breast Ultrasound Image Augmentation
Farhan Fuad Abir, Sanjeda Sara Jennifer, Niloofar Yousefi +1
We propose a hybrid diffusion-based augmentation framework to overcome the critical challenge of ultrasound data augmentation in breast ultrasound (BUS) datasets. Unlike convention…
BiSe-Unet: A Lightweight Dual-path U-Net with Attention-refined Context for Real-time Medical Image Segmentation
M Iffat Hossain, Laura Brattain
During image-guided procedures, real-time image segmentation is often required. This demands lightweight AI models that can operate on resource-constrained devices. One important u…
Fourier Transform Multiple Instance Learning for Whole Slide Image Classification
Anthony Bilic, Guangyu Sun, Ming Li +6
Whole Slide Image (WSI) classification relies on Multiple Instance Learning (MIL) with spatial patch features, yet existing methods struggle to capture global dependencies due to t…
Multimodal Deep Learning for Phyllodes Tumor Classification from Ultrasound and Clinical Data
Farhan Fuad Abir, Abigail Elliott Daly, Kyle Anderman +2
Phyllodes tumors (PTs) are rare fibroepithelial breast lesions that are difficult to classify preoperatively due to their radiological similarity to benign fibroadenomas. This ofte…
A Synoptic Review of High-Frequency Oscillations as a Biomarker in Neurodegenerative Disease
Samin Yaser, Mahad Ali, Yang Jiang +3
High Frequency Oscillations (HFOs), rapid bursts of brain activity above 80 Hz, have emerged as a highly specific biomarker for epileptogenic tissue. Recent evidence suggests that…
T2ID-CAS: Diffusion Model and Class Aware Sampling to Mitigate Class Imbalance in Neck Ultrasound Anatomical Landmark Detection
Manikanta Varaganti, Amulya Vankayalapati, Nour Awad +2
Neck ultrasound (US) plays a vital role in airway management by providing non-invasive, real-time imaging that enables rapid and precise interventions. Deep learning-based anatomic…
Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions
Gulsah Hancerliogullari Koksalmis, Bulent Soykan, Laura J. Brattain +1
Alzheimer's Disease (AD) is marked by significant inter-individual variability in its progression, complicating accurate prognosis and personalized care planning. This heterogeneit…
Fine-Tuning Foundation Models with Federated Learning for Privacy Preserving Medical Time Series Forecasting
Mahad Ali, Curtis Lisle, Patrick W. Moore +3
Federated Learning (FL) provides a decentralized machine learning approach, where multiple devices or servers collaboratively train a model without sharing their raw data, thus ena…
Point Cloud Context Analysis for Rehabilitation Grasping Assistance
Jackson M. Steinkamp, Laura J. Brattain, Conor J. Walsh +1
Controlling hand exoskeletons for assisting impaired patients in grasping tasks is challenging because it is difficult to infer user intent. We hypothesize that majority of daily g…
Improved Topological Preservation in 3D Axon Segmentation and Centerline Detection using Geometric Assessment-driven Topological Smoothing (GATS)
Nina I. Shamsi, Alex S. Xu, Lars A. Gjesteby +1
Automated axon tracing via fully supervised learning requires large amounts of 3D brain imagery, which is time consuming and laborious to obtain. It also requires expertise. Thus,…
Developing a Series of AI Challenges for the United States Department of the Air Force
Vijay Gadepally, Gregory Angelides, Andrei Barbu +39
Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have…
Active Learning Pipeline for Brain Mapping in a High Performance Computing Environment
Adam Michaleas, Lars A. Gjesteby, Michael Snyder +10
This paper describes a scalable active learning pipeline prototype for large-scale brain mapping that leverages high performance computing power. It enables high-throughput evaluat…
Self-Supervised Feature Extraction for 3D Axon Segmentation
Tzofi Klinghoffer, Peter Morales, Young-Gyun Park +3
Existing learning-based methods to automatically trace axons in 3D brain imagery often rely on manually annotated segmentation labels. Labeling is a labor-intensive process and is…
Benchmarking SciDB Data Import on HPC Systems
Siddharth Samsi, Laura Brattain, William Arcand +16
SciDB is a scalable, computational database management system that uses an array model for data storage. The array data model of SciDB makes it ideally suited for storing and manag…