399 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Rice UniversityUS17 papers
- The University of Texas Health Science Center at HoustonUS17 papers
- The University of Texas at AustinUS13 papers
- Harvard UniversityUS12 papers
- Baylor College of MedicineUS10 papers
- The University of Texas Southwestern Medical CenterUS9 papers
- University of PennsylvaniaUS8 papers
- Massachusetts General HospitalUS7 papers
- Stanford UniversityUS7 papers
- Technical University of MunichDE7 papers
- University of Alabama at BirminghamUS7 papers
- University of North Carolina at Chapel HillUS7 papers
175 papers
Ridge-filter crosstalk in conformal proton FLASH planning: dependence on beamlet pitch and iterative mitigation
Zongsheng Hu, Yuting Li, Henry Meyer +5
Objective: Patient-specific ridge filters (PSRFs) can enable conformal single-energy proton FLASH delivery without energy switching. However, converting optimized spot-based dose d…
Synthetic Melanoma Image Generation and Evaluation Using Generative Adversarial Networks
Pei-Yu Lin, Yidan Shen, Neville Mathew +6
Melanoma is the most lethal form of skin cancer, and early detection is critical for improving patient outcomes. Although dermoscopy combined with deep learning has advanced automa…
Bi-level Multi-criteria Optimization for Risk-informed Radiotherapy
Mara Schubert, Katrin Teichert, Zhongxing Liao +2
In radiation therapy (RT) treatment planning, multi-criteria optimization (MCO) supports efficient plan selection but is usually solved for population-based dosimetric criteria and…
Foundation Models in Biomedical Imaging: Turning Hype into Reality
Amgad Muneer, Kai Zhang, Ibraheem Hamdi +6
Foundation models (FMs) are driving a prominent shift in biomedical imaging from task-specific models to unified backbone models for diverse tasks. This opens an avenue to integrat…
Patch Progression Masked Autoencoder with Fusion CNN Network for Classifying Evolution Between Two Pairs of 2D OCT Slices
Philippe Zhang, Weili Jiang, Yihao Li +13
Age-related Macular Degeneration (AMD) is a prevalent eye condition affecting visual acuity. Anti-vascular endothelial growth factor (anti-VEGF) treatments have been effective in s…
The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology
Muhammad Waqas, Rukhmini Bandyopadhyay, Eman Showkatian +12
Foundation models have recently emerged as powerful feature extractors in computational pathology, yet they typically omit mechanisms for leveraging the global spatial structure of…
Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion
Jorge Tapias Gomez, Nishant Nadkarni, Lando S. Bosma +7
Objective: Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging…
From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research
Amgad Muneer, Muhammad Waqas, Maliazurina B Saad +16
Cancer research is increasingly driven by the integration of diverse data modalities, spanning from genomics and proteomics to imaging and clinical factors. However, extracting act…
Synthesized Annotation Guidelines are Knowledge-Lite Boosters for Clinical Information Extraction
Enshuo Hsu, Martin Ugbala, Krishna Kumar Kookal +4
Generative information extraction using large language models, particularly through few-shot learning, has become a popular method. Recent studies indicate that providing a detaile…
Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?
Hye Sun Yun, Karen Y. C. Zhang, Ramez Kouzy +3
Medical research faces well-documented challenges in translating novel treatments into clinical practice. Publishing incentives encourage researchers to present "positive" findings…
Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases
Jacob J. Peoples, Mohammad Hamghalam, Imani James +7
Establishing the reproducibility of radiomic signatures is a critical step in the path to clinical adoption of quantitative imaging biomarkers; however, radiomic signatures must al…
Bayesian Clustering Prior with Overlapping Indices for Effective Use of Multisource External Data
Xuetao Lu, J. Jack Lee
The use of external data in clinical trials offers numerous advantages, such as reducing the number of patients, increasing study power, and shortening trial durations. In Bayesian…
Bayesian Transfer Learning for Enhanced Estimation and Inference
Daoyuan Lai, Oscar Hernan Madrid Padilla, Xiang Li +1
Transfer learning enhances model performance in a target population with limited samples by leveraging knowledge from related studies. While many works focus on improving predictiv…
LLM-IE: A Python Package for Generative Information Extraction with Large Language Models
Enshuo Hsu, Kirk Roberts
Objectives: Despite the recent adoption of large language models (LLMs) for biomedical information extraction, challenges in prompt engineering and algorithms persist, with no dedi…
Robust multi-coil MRI reconstruction via self-supervised denoising
Asad Aali, Marius Arvinte, Sidharth Kumar +2
We study the effect of incorporating self-supervised denoising as a pre-processing step for training deep learning (DL) based reconstruction methods on data corrupted by Gaussian n…
Clustering Computer Mouse Tracking Data with Informed Hierarchical Shrinkage Partition Priors
Ziyi Song, Weining Shen, Marina Vannucci +4
Mouse-tracking data, which record computer mouse trajectories while participants perform an experimental task, provide valuable insights into subjects' underlying cognitive process…
OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment
Lucas McCullum, Kareem A. Wahid, Barbara Marquez +1
The Dice Similarity Coefficient (DSC) is the current de facto standard to determine agreement between a reference segmentation and one generated by manual / auto-contouring approac…
Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image Segmentation
McKell Woodland, Nihil Patel, Austin Castelo +13
Clinically deployed deep learning-based segmentation models are known to fail on data outside of their training distributions. While clinicians review the segmentations, these mode…
ROMI: A Randomized Two-Stage Basket Trial Design to Optimize Doses for Multiple Indications
Shuqi Wang, Peter F. Thall, Kentaro Takeda +1
Optimizing doses for multiple indications is challenging. The pooled approach of finding a single optimal biological dose (OBD) for all indications ignores that dose-response or do…
Mimicking large spot-scanning radiation fields for proton FLASH preclinical studies with a robotic motion platform
Fada Guan, Dadi Jiang, Xiaochun Wang +12
Previously, a synchrotron-based horizontal proton beamline (87.2 MeV) was successfully commissioned to deliver radiation doses in FLASH and conventional dose rate modes to small fi…
Conformal predictive intervals in survival analysis: a re-sampling approach
Jing Qin, Jin Piao, Jing Ning +1
The distribution-free method of conformal prediction (Vovk et al, 2005) has gained considerable attention in computer science, machine learning, and statistics. Candes et al. (2023…
Leveraging Large Language Models for Knowledge-free Weak Supervision in Clinical Natural Language Processing
Enshuo Hsu, Kirk Roberts
The performance of deep learning-based natural language processing systems is based on large amounts of labeled training data which, in the clinical domain, are not easily availabl…
On the acceptance, commissioning, and quality assurance of electron FLASH units
Allison Palmiero, Kevin Liu, Julie Colnot +15
Background & Purpose: FLASH or ultra-high dose rate (UHDR) radiation therapy (RT) has gained attention in recent years for its ability to spare normal tissues relative to conventio…
Relation Extraction Using Large Language Models: A Case Study on Acupuncture Point Locations
Yiming Li, Xueqing Peng, Jianfu Li +6
In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like…