10 citations · 14 across the 18 of their papers we have counts for
6 papers · 1 filter
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…