40.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of CincinnatiUS19 papers
- University of Cincinnati Medical CenterUS8 papers
- University of PennsylvaniaUS4 papers
- Children's Hospital of PhiladelphiaUS3 papers
- Harvard UniversityUS3 papers
- Rutgers, The State University of New JerseyUS3 papers
- University of California, Los AngelesUS3 papers
- University of California San DiegoUS3 papers
- University of CambridgeGB3 papers
- University of Wisconsin–MadisonUS3 papers
- Yale UniversityUS3 papers
- Amrita Vishwa VidyapeethamIN2 papers
36 papers
Graph-Based Approaches to Learning Epileptogenic Zone Localization Using Stereo-EEG Recordings
Daniel Wendelken, Brian Ervin, Ravindra Arya +1
The epileptogenic zone (EZ) is the brain region that generates seizures in an individual, and is the target of epilepsy surgery. Localizing the EZ from stereo-EEG (sEEG) recordings…
Computer Vision Based Neurology Brain Activity Rejection Architecture and Implementation
Zag ElSayed, Nathan Suer, Grace Westerkamp +4
The electroencephalogram (EEG) is a valuable and widely applied tool for investigating brain disorders and behavioral changes. It offers a minimally restrictive and non-invasive me…
A Bayesian location-scale joint model for time-to-event and multivariate longitudinal data with association based on within-individual variability
Marco Palma, Ruth H Keogh, Siobhán B Carr +5
Within-individual variability of health indicators measured over time is becoming commonly used to inform about disease progression. Simple summary statistics (e.g. the standard de…
Environment Scan of Generative AI Infrastructure for Clinical and Translational Science
Betina Idnay, Zihan Xu, William G. Adams +54
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 instituti…
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu +77
Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%.…
A joint model for (un)bounded longitudinal markers, competing risks, and recurrent events using patient registry data
Pedro Miranda Afonso, Dimitris Rizopoulos, Anushka K. Palipana +5
Joint models for longitudinal and survival data have become a popular framework for studying the association between repeatedly measured biomarkers and clinical events. Nevertheles…
RadCLIP: Enhancing Radiologic Image Analysis through Contrastive Language-Image Pre-training
Zhixiu Lu, Hailong Li, Nehal A. Parikh +2
The integration of artificial intelligence (AI) with radiology marks a transformative era in medicine. Vision foundation models have been adopted to enhance radiologic imaging anal…
Joint Self-Supervised and Supervised Contrastive Learning for Multimodal MRI Data: Towards Predicting Abnormal Neurodevelopment
Zhiyuan Li, Hailong Li, Anca L. Ralescu +5
The integration of different imaging modalities, such as structural, diffusion tensor, and functional magnetic resonance imaging, with deep learning models has yielded promising ou…
Accelerating and scaling mentoring strategies to build infrastructure that supports underrepresented groups in STEM
2030STEM Collaboration, Jennifer D. Adams, David Asai +13
The vision of 2030STEM is to address systemic barriers in institutional structures and funding mechanisms required to achieve full inclusion in Science, Technology, Engineering, an…
A Novel Collaborative Self-Supervised Learning Method for Radiomic Data
Zhiyuan Li, Hailong Li, Anca L. Ralescu +3
The computer-aided disease diagnosis from radiomic data is important in many medical applications. However, developing such a technique relies on annotating radiological images, wh…
Federated learning: Applications, challenges and future directions
Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder +1
Federated learning (FL) is a system in which a central aggregator coordinates the efforts of multiple clients to solve machine learning problems. This setting allows training data…
A Novel Ontology-guided Attribute Partitioning Ensemble Learning Model for Early Prediction of Cognitive Deficits using Quantitative Structural MRI in Very Preterm Infants
Zhiyuan Li, Hailong Li, Adebayo Braimah +3
Structural magnetic resonance imaging studies have shown that brain anatomical abnormalities are associated with cognitive deficits in preterm infants. Brain maturation and geometr…
Dynamic imaging using Motion-Compensated SmooThness Regularization on Manifolds (MoCo-SToRM)
Qing Zou, Luis A. Torres, Sean B. Fain +3
We introduce an unsupervised motion-compensated reconstruction scheme for high-resolution free-breathing pulmonary MRI. We model the image frames in the time series as the deformed…
Measuring information exchange and brokerage capacity of healthcare teams
F. Grippa, J. Bucuvalas, A. Booth +3
Purpose: The purpose of this paper is to explore possible factors impacting team performance in healthcare, by focusing on information exchange within and across hospital's boundar…
Fast Nonblocking Persistence for Concurrent Data Structures
Wentao Cai, Haosen Wen, Vladimir Maksimovski +4
We present a fully lock-free variant of the recent Montage system for persistent data structures. Our variant, nbMontage, adds persistence to almost any nonblocking concurrent stru…
Deep Learning Approach for Enhanced Cyber Threat Indicators in Twitter Stream
Simran K, Prathiksha Balakrishna, Vinayakumar R +1
In recent days, the amount of Cyber Security text data shared via social media resources mainly Twitter has increased. An accurate analysis of this data can help to develop cyber t…
Deep Learning Approach for Intelligent Named Entity Recognition of Cyber Security
Simran K, Sriram S, Vinayakumar R +1
In recent years, the amount of Cyber Security data generated in the form of unstructured texts, for example, social media resources, blogs, articles, and so on has exceptionally in…
Source-specific contributions of particulate matter to asthma-related pediatric emergency department utilization
Mohammad Alfrad Nobel Bhuiyan, Patrick Ryan, Farzan Oroumyeh +4
Few studies have linked specific sources of ambient particulate matter smaller than 2.5 m (PM2.5) and asthma. In this study, we estimated the contributions of specific sources t…
Bayesian Shape Invariant Model for Latent Growth Curve with Time-Invariant Covariates
Mohammad Alfrad Nobel Bhuiyan, Heidi Sucharew, Rhonda Szczesniak +4
In the attention-deficit hyperactivity disorder (ADHD) study, children are prescribed different stimulant medications. The height measurements are recorded longitudinally along wit…
Efficiency of Observed Information Adaptive Designs
Adam Lane
In this work the primary objective is to maximize the precision of the maximum likelihood estimate in a linear regression model through the efficient design of the experiment. One…
Guidelines for reporting single-cell RNA-Seq experiments
Anja Füllgrabe, Nancy George, Matthew Green +16
Single-cell RNA-Sequencing (scRNA-Seq) has undergone major technological advances in recent years, enabling the conception of various organism-level cell atlassing projects. With i…
Conditional Information and Inference in Response-Adaptive Allocation Designs
Adam Lane
Response-adaptive allocation designs refer to a class of designs where the probability an observation is assigned to a treatment is changed throughout an experiment based on the ac…
SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
Pauli Virtanen, Ralf Gommers, Travis E. Oliphant +32
SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release…
GPMatch: A Bayesian Doubly Robust Approach to Causal Inference with Gaussian Process Covariance Function As a Matching Tool
Bin Huang, Chen Chen, Jinzhong Liu
Gaussian process (GP) covariance function is proposed as a matching tool in GPMatch within a full Bayesian framework under relatively weaker causal assumptions. The matching is acc…