30 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Emory UniversityUS9 papers
- Georgia Institute of TechnologyUS8 papers
- University of Wisconsin–MadisonUS3 papers
- Aflac (United States)US2 papers
- Jacobs (United States)US2 papers
- Roswell Park Comprehensive Cancer CenterUS2 papers
- The Wallace H. Coulter Department of Biomedical EngineeringUS2 papers
- University of California, RiversideUS2 papers
- University of Wisconsin Carbone Cancer CenterUS2 papers
- Association for Computing MachineryUS1 paper
- Chemnitz University of TechnologyDE1 paper
- ETH ZurichCH1 paper
12 papers
A Computational Journey Toward an Optimal Design for Metamaterial Epicardial Passive Sleeves
Vahid Naeini, Emilio A. Mendiola, Ahmad Rafsanjani +6
Heart failure (HF) following myocardial infarction (MI) is a major clinical challenge with severe complications. Epicardial sleeves and patches are increasingly investigated to imp…
CARE-SD: Classifier-based analysis for recognizing and eliminating stigmatizing and doubt marker labels in electronic health records: model development and validation
Drew Walker, Annie Thorne, Sudeshna Das +4
Objective: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques. Mate…
Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network
Xin Tie, Muheon Shin, Changhee Lee +10
: Automatic quantification of longitudinal changes in PET scans for lymphoma patients has proven challenging, as residual disease in interim-therapy scans is ofte…
Automatic Personalized Impression Generation for PET Reports Using Large Language Models
Xin Tie, Muheon Shin, Ali Pirasteh +8
In this study, we aimed to determine if fine-tuned large language models (LLMs) can generate accurate, personalized impressions for whole-body PET reports. Twelve language models w…
Social Phases in Human Movement
Yi Zhang, Debasish Sarker, Samantha Mitsven +3
Recent empirical studies found different thermodynamic phases for collective motion in animals. However, such a thermodynamic description for human movement remains unclear, mainly…
Early in vivo Radiation Damage Quantification for Pediatric Craniospinal Irradiation Using Longitudinal MRI for Intensity Modulated Proton Therapy
Chih-Wei Chang, Matt Goette, Nadja Kadom +8
Purpose: Proton vertebral body sparing craniospinal irradiation (VBS CSI) treats the thecal sac while avoiding the anterior vertebral bodies in effort to reduce myelosuppression an…
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units
Shenda Hong, Yanbo Xu, Alind Khare +5
Deep learning models have achieved expert-level performance in healthcare with an exclusive focus on training accurate models. However, in many clinical environments such as intens…
Flow-induced segregation and dynamics of red blood cells in sickle cell disease
Xiao Zhang, Christina Caruso, Wilbur A. Lam +1
Blood flow in sickle cell disease (SCD) can substantially differ from normal blood flow due to significant alterations in the physical properties of the red blood cells (RBCs). Chr…
RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data
Yanbo Xu, Siddharth Biswal, Shriprasad R Deshpande +2
With the improvement of medical data capturing, vast amount of continuous patient monitoring data, e.g., electrocardiogram (ECG), real-time vital signs and medications, become avai…
COPA: Constrained PARAFAC2 for Sparse & Large Datasets
Ardavan Afshar, Ioakeim Perros, Evangelos E. Papalexakis +3
PARAFAC2 has demonstrated success in modeling irregular tensors, where the tensor dimensions vary across one of the modes. An example scenario is modeling treatments across a set o…
SPARTan: Scalable PARAFAC2 for Large & Sparse Data
Ioakeim Perros, Evangelos E. Papalexakis, Fei Wang +4
In exploratory tensor mining, a common problem is how to analyze a set of variables across a set of subjects whose observations do not align naturally. For example, when modeling m…
Multi-layer Representation Learning for Medical Concepts
Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles +2
Learning efficient representations for concepts has been proven to be an important basis for many applications such as machine translation or document classification. Proper repres…