390 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of OxfordGB9 papers
- Rowan UniversityUS8 papers
- Harvard UniversityUS4 papers
- University of PennsylvaniaUS4 papers
- Chalmers University of TechnologySE3 papers
- Georgetown UniversityUS3 papers
- University of Alabama at BirminghamUS3 papers
- University of GothenburgSE3 papers
- Vanderbilt UniversityUS3 papers
- Baylor College of MedicineUS2 papers
- Brigham and Women's HospitalUS2 papers
- Carnegie Mellon UniversityUS2 papers
43 papers
CancerKG.ORG A Web-scale, Interactive, Verifiable Knowledge Graph-LLM Hybrid for Assisting with Optimal Cancer Treatment and Care
Michael Gubanov, Anna Pyayt, Aleksandra Karolak
Here, we describe one of the first Web-scale hybrid Knowledge Graph (KG)-Large Language Model (LLM), populated with the latest peer-reviewed medical knowledge on colorectal Cancer.…
Improving Radiology Report Conciseness and Structure via Local Large Language Models
Iryna Hartsock, Cyrillo Araujo, Les Folio +1
Radiology reports are often lengthy and unstructured, posing challenges for referring physicians to quickly identify critical imaging findings while increasing the risk of missed i…
Vision-Language Models for Medical Report Generation and Visual Question Answering: A Review
Iryna Hartsock, Ghulam Rasool
Medical vision-language models (VLMs) combine computer vision (CV) and natural language processing (NLP) to analyze visual and textual medical data. Our paper reviews recent advanc…
Antifragility as a complex system's response to perturbations, volatility, and time
Cristian Axenie, Oliver López-Corona, Michail A. Makridis +4
Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifie…
Modeling non-genetic information dynamics in cells using reservoir computing
Dipesh Niraula, Issam El Naqa, Jack Adam Tuszynski +1
Virtually all cells use energy and ion-specific membrane pumps to maintain large transmembrane gradients of Na, K, Cl, Mg, and Ca. Although they consume u…
Revisiting the Fragility of Influence Functions
Jacob R. Epifano, Ravi P. Ramachandran, Aaron J. Masino +1
In the last few years, many works have tried to explain the predictions of deep learning models. Few methods, however, have been proposed to verify the accuracy or faithfulness of…
EvalAttAI: A Holistic Approach to Evaluating Attribution Maps in Robust and Non-Robust Models
Ian E. Nielsen, Ravi P. Ramachandran, Nidhal Bouaynaya +2
The expansion of explainable artificial intelligence as a field of research has generated numerous methods of visualizing and understanding the black box of a machine learning mode…
Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review
Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran +2
Cancer has relational information residing at varying scales, modalities, and resolutions of the acquired data, such as radiology, pathology, genomics, proteomics, and clinical rec…
Efficient Scopeformer: Towards Scalable and Rich Feature Extraction for Intracranial Hemorrhage Detection
Yassine Barhoumi, Nidhal C. Bouaynaya, Ghulam Rasool
The quality and richness of feature maps extracted by convolution neural networks (CNNs) and vision Transformers (ViTs) directly relate to the robust model performance. In medical…
Working With Convex Responses: Antifragility From Finance to Oncology
Nassim Nicholas Taleb, Jeffrey West
We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology where it can inform dosing and interventio…
Topological and metric properties of spaces of generalized persistence diagrams
Peter Bubenik, Iryna Hartsock
Motivated by persistent homology and topological data analysis, we consider formal sums on a metric space with a distinguished subset. These formal sums, which we call persistence…
Transformers in Time-series Analysis: A Tutorial
Sabeen Ahmed, Ian E. Nielsen, Aakash Tripathi +3
Transformer architecture has widespread applications, particularly in Natural Language Processing and computer vision. Recently Transformers have been employed in various aspects o…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
SUPER-Net: Trustworthy Image Segmentation via Uncertainty Propagation in Encoder-Decoder Networks
Giuseppina Carannante, Nidhal C. Bouaynaya, Dimah Dera +2
Deep Learning (DL) holds great promise in reshaping the industry owing to its precision, efficiency, and objectivity. However, the brittleness of DL models to noisy and out-of-dist…
Interpretable Visual Understanding with Cognitive Attention Network
Xuejiao Tang, Wenbin Zhang, Yi Yu +4
While image understanding on recognition-level has achieved remarkable advancements, reliable visual scene understanding requires comprehensive image understanding on recognition-l…
Improving the efficiency of small animal 3D printed compensator IMRT with beamlet intensity total variation regularization
Xinmin Liu, Alexander L. Van Slyke, Erik Pearson +3
Purpose: There is growing interest in the use of modern 3D printing technology to implement intensity-modulated radiation therapy (IMRT) on the preclinical scale which is analogous…
Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks
Ian E. Nielsen, Dimah Dera, Ghulam Rasool +2
With the rise of deep neural networks, the challenge of explaining the predictions of these networks has become increasingly recognized. While many methods for explaining the decis…
Exploring Robust Architectures for Deep Artificial Neural Networks
Asim Waqas, Ghulam Rasool, Hamza Farooq +1
The architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance. However, the relationship between the architecture of a…
Ten Quick Tips for Deep Learning in Biology
Benjamin D. Lee, Anthony Gitter, Casey S. Greene +17
Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that…
Super-Linear Growth Reveals the Allee Effect in Tumors
Youness Azimzade, Abbas Ali Saberi, Robert A. Gatenby
Integrating experimental data into ecological models plays a central role in understanding biological mechanisms that drive tumor progression where such knowledge can be used to de…
Outcome-guided Sparse K-means for Disease Subtype Discovery via Integrating Phenotypic Data with High-dimensional Transcriptomic Data
Lingsong Meng, Dorina Avram, George Tseng +1
The discovery of disease subtypes is an essential step for developing precision medicine, and disease subtyping via omics data has become a popular approach. While promising, subty…
Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet
Sara Ranjbar, Kyle W. Singleton, Lee Curtin +5
Whole brain extraction, also known as skull stripping, is a process in neuroimaging in which non-brain tissue such as skull, eyeballs, skin, etc. are removed from neuroimages. Skul…
A comparative study between discrete and continuum models for the evolution of competing phenotype-structured cell populations in dynamical environments
Aleksandra Ardaševa, Robert A. Gatenby, Alexander R. A. Anderson +3
Deterministic continuum models formulated in terms of non-local partial differential equations for the evolutionary dynamics of populations structured by phenotypic traits have bee…
On the pressure equilibrium and timescales in the scale free convection theory
Stefano Pasetto, Cesare Chiosi, Mark Cropper +2
Convection is one of the fundamental energy transport processes in physics and astrophysics, and its description is central to allstellar models. In the context of stellar astrophy…