Bioterrorism

IGNIS: A Neural Network Framework for Robust Parameter Estimation in Archimedean Copulas

Parameter estimation for Archimedean copulas remains a challenging problem, particularly for the recently developed A1 and A2 families that exhibit complex dependency structures. Traditional methods, such as the Method of Moments (MoM), Maximum Likelihood Estimation (MLE), and Maximum Pseudo-Likelihood (MPL), often struggle due to issues of non-monotonic relationship with dependency measures suc...

Leveraging Interview-Informed LLMs to Model Survey Responses: Comparative Insights from AI-Generated and Human Data

Mixed methods research integrates quantitative and qualitative data but faces challenges in aligning their distinct structures, particularly in examining measurement characteristics and individual response patterns. Advances in large language models (LLMs) offer promising solutions by generating synthetic survey responses informed by qualitative data. This study investigates whether LLMs, guided...

SAGE-Eval: Evaluating LLMs for Systematic Generalizations of Safety Facts

Do LLMs robustly generalize critical safety facts to novel situations? Lacking this ability is dangerous when users ask naive questions. For instanc...

RoofNet: A Global Multimodal Dataset for Roof Material Classification

Natural disasters are increasing in frequency and severity, causing hundreds of billions of dollars in damage annually and posing growing threats to...

DanceTogether! Identity-Preserving Multi-Person Interactive Video Generation

Controllable video generation (CVG) has advanced rapidly, yet current systems falter when more than one actor must move, interact, and exchange posi...

Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding

In this work, we propose Dimple, the first Discrete Diffusion Multimodal Large Language Model (DMLLM). We observe that training with a purely discre...

Predicting Neo-Adjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic Images

Triple-negative breast cancer (TNBC) is an aggressive subtype defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human e...

Higher fidelity perceptual image and video compression with a latent conditioned residual denoising diffusion model

Denoising diffusion models achieved impressive results on several image generation tasks often outperforming GAN based models. Recently, the generat...

Deep learning progressive distill for predicting clinical response to conversion therapy from preoperative CT images of advanced gastric cancer patients.

Identifying patients suitable for conversion therapy through early non-invasive screening is crucial for tailoring treatment in advanced gastric cance...

Enhanced effective convolutional attention network with squeeze-and-excitation inception module for multi-label clinical document classification.

Clinical Document Classification (CDC) is crucial in healthcare for organizing and categorizing large volumes of medical information, leading to impro...

Pros, Cons and Limits of AI in Public Health.

This paper explores the role of Artificial Intelligence (AI) in Public Health (PH), examining its benefits, challenges, and ethical considerations. AI...

Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting

Typhoon trajectory forecasting is essential for disaster preparedness but remains computationally demanding due to the complexity of atmospheric dyn...

Modeling heterogeneity, commitment, and memory of bacterial spore germination.

Spores of bacteria are metabolically dormant, resistant to microbicides, and vectors of food spoilage and diseases and survive for years in their dorm...

Diagnostic Excellence: An Opportunity, and Call to Action, for Radiologists.

In late 2024, the CDC released a statement on diagnostic excellence in healthcare. Diagnostic excellence encompasses process improvements in radiology...

Exploring the Opportunities and Challenges of Healthcare Innovation in UK Higher Education: A Narrative Review.

: The healthcare sector is under increasing pressure due to an ageing population, rising multimorbidity, and a projected global workforce shortage of ...

The Role of Artificial Intelligence in Drug Discovery and Pharmaceutical Development: A Paradigm Shift in the History of Pharmaceutical Industries.

In today's world, with an increasing patient population, the need for medications is increasing rapidly. However, the current practice of drug develop...

Signal-based AI-driven software solution for automated quantification of metastatic bone disease and treatment response assessment using Whole-Body Diffusion-Weighted MRI (WB-DWI) biomarkers in Advanced Prostate Cancer

We developed an AI-driven software solution to quantify metastatic bone disease from WB-DWI scans. Core technologies include: (i) a weakly-supervise...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) cou...

Rapid Response System Restructure: Focus on Prevention and Early Intervention.

This article describes the staged restructure of the rapid response program into a dedicated 24/7 proactive rapid response system in a quaternary acad...

Can American Board of Surgery in Training Examinations be passed by Large Language Models? Comparative assessment of Gemini, Copilot, and ChatGPT.

ObjectiveThis study aimed to evaluate the performance of large language models (LLMs) in answering questions from the American Board of Surgery In-Tra...