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
18 papers · 1 filter
Optimal Bayesian hierarchical model to accelerate the development of tissue-agnostic drugs and basket trials
Liyun Jiang, Lei Nie, Fangrong Yan +1
Tissue-agnostic trials enroll patients based on their genetic biomarkers, not tumor type, in an attempt to determine if a new drug can successfully treat disease conditions based o…
A Note on Bayesian Modeling Specification of Censored Data in JAGS
Xinyue Qi, Shouhao Zhou, Martyn Plummer
Just Another Gibbs Sampling (JAGS) is a convenient tool to draw posterior samples using Markov Chain Monte Carlo for Bayesian modeling. However, the built-in function dinterval() t…
A Framework for Mediation Analysis with Multiple Exposures, Multivariate Mediators, and Non-Linear Response Models
James P. Long, Ehsan Irajizad, James D. Doecke +2
Mediation analysis seeks to identify and quantify the paths by which an exposure affects an outcome. Intermediate variables which are effected by the exposure and which effect the…
Plasmonic nano-aperture label-free imaging
Nareg Ohannesian, Ibrahim Misbah, Steven H Lin +1
Label-free observation of nanoparticles by far-field optical microscopy is challenging because their ability to scatter or absorb light dramatically diminishes with decreasing size…
Beam data modeling of linear accelerators (linacs) through machine learning and its potential applications in fast and robust linac commissioning and quality assurance
Wei Zhao, Ishan Patil, Bin Han +3
Background and purpose: To propose a novel machine learning-based method for reliable and accurate modeling of linac beam data applicable to the processes of linac commissioning an…
Oxygen depletion in FLASH ultra-high-dose-rate radiotherapy: A molecular dynamics simulation
Ramin Abolfath, David Grosshans, Radhe Mohan
We present a first-principles molecular dynamics (MD) simulation and expound upon a mechanism of oxygen depletion hypothesis to explain the mitigation of normal tissue injury obser…
Elastic Priors to Dynamically Borrow Information from Historical Data in Clinical Trials
Liyun Jiang, Lei Nie, Ying Yuan
Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is how to effectively borrow information from…
Evaluation of the Visibility and Artifacts of 11 Common Fiducial Markers for Image-Guided Stereotactic Body Radiation Therapy in the Abdomen
Jordan M. Slagowski, Lauren E. Colbert, Irina M. Cazacu +8
The purpose of this study was to quantitatively evaluate the visibility and artifacts of commercially available fiducial markers in order to optimize their selection for image-guid…
A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
Md. Milon Islam, Fakhri Karray, Reda Alhajj +1
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world and has become one of the most acute and severe ailments in the past hundred years. The…
Design of phase III trials with long-term survival outcomes based on short-term binary results
Marta Bofill Roig, Yu Shen, Guadalupe Gómez Melis
Pathologic complete response (pCR) is a common primary endpoint for a phase II trial or even accelerated approval of neoadjuvant cancer therapy. If granted, a two-arm confirmatory…
Sparse tree-based clustering of microbiome data to characterize microbiome heterogeneity in pancreatic cancer
Yushu Shi, Liangliang Zhang, Kim-Anh Do +2
There is a keen interest in characterizing variation in the microbiome across cancer patients, given increasing evidence of its important role in determining treatment outcomes. He…
3D source tracking and error detection in HDR using two independent scintillator dosimetry systems
Haydee M. Linares Rosales, Jacob G. Johansen, Gustavo Kertzscher +3
The high dose gradients near the source characteristics of brachytherapy are equivalent to nefarious effects if unnoticed errors take place during the patient treatment. In vivo do…
A modular phantom and software to characterize 3D geometric distortion in MRI
Jordan M. Slagowski, Yao Ding, Manik Aima +8
MRI offers outstanding soft tissue contrast that may reduce uncertainties in target and organ-at-risk delineation and enable online adaptive image-guided treatment. Spatial distort…
A New Approach to Modeling the Microdosimetry of Proton Therapy Beams
Ramin Abolfath, Yusuf Helo, David J. Carlson +3
{\bf Introduction}: To revisit the formulation of the mean chord length in microdosimetry and replace it by the particle mean free path appropriate for modelings in radio-biology.…
aPCoA: Covariate Adjusted Principal Coordinates Analysis
Yushu Shi, Liangliang Zhang, Kim-Anh Do +2
In fields such as ecology, microbiology, and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances…
A Bayesian Feature Allocation Model for Identification of Cell Subpopulations Using Cytometry Data
Arthur Lui, Juhee Lee, Peter F. Thall +3
A Bayesian feature allocation model (FAM) is presented for identifying cell subpopulations based on multiple samples of cell surface or intracellular marker expression level data o…
A DNA damage multi-scale model for NTCP in proton and hadron therapy
Ramin Abolfath, Chris Peeler, Dragan Mirkovic +2
{\bf Purpose}: To develop a first principle and multi-scale model for normal tissue complication probability (NTCP) as a function of dose and LET for proton and in general for part…
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat +66
Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit cl…