Clinical Trials

Recommending Clinical Trials for Online Patient Cases using Artificial Intelligence

Clinical trials are crucial for assessing new treatments; however, recruitment challenges - such as limited awareness, complex eligibility criteria, and referral barriers - hinder their success. With the growth of online platforms, patients increasingly turn to social media and health communities for support, research, and advocacy, expanding recruitment pools and established enrollment pathways...

Efficient and Robust Remote Sensing Image Denoising Using Randomized Approximation of Geodesics' Gramian on the Manifold Underlying the Patch Space

Remote sensing images are widely utilized in many disciplines such as feature recognition and scene semantic segmentation. However, due to environmental factors and the issues of the imaging system, the image quality is often degraded which may impair subsequent visual tasks. Even though denoising remote sensing images plays an essential role before applications, the current denoising algorithms...

LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models

Recent advancements in Large Language Models (LLMs) have enabled them to approach human-level persuasion capabilities. However, such potential also ...

Do We Really Need Curated Malicious Data for Safety Alignment in Multi-modal Large Language Models?

Multi-modal large language models (MLLMs) have made significant progress, yet their safety alignment remains limited. Typically, current open-source...

The Structural Safety Generalization Problem

LLM jailbreaks are a widespread safety challenge. Given this problem has not yet been tractable, we suggest targeting a key failure mechanism: the f...

A Two-Stage Interpretable Matching Framework for Causal Inference

Matching in causal inference from observational data aims to construct treatment and control groups with similar distributions of covariates, thereb...

CamMimic: Zero-Shot Image To Camera Motion Personalized Video Generation Using Diffusion Models

We introduce CamMimic, an innovative algorithm tailored for dynamic video editing needs. It is designed to seamlessly transfer the camera motion obs...

Dose-finding design based on level set estimation in phase I cancer clinical trials

The primary objective of phase I cancer clinical trials is to evaluate the safety of a new experimental treatment and to find the maximum tolerated ...

Using Vision Language Models for Safety Hazard Identification in Construction

Safety hazard identification and prevention are the key elements of proactive safety management. Previous research has extensively explored the appl...

Benchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-Judge

Large Language Models (LLMs) have revolutionized artificial intelligence, driving advancements in machine translation, summarization, and conversati...

Building Proactive and Instant-Reactive Safety Designs to Address Harassment in Social Virtual Reality

Social Virtual Reality (VR) games offer immersive socialization experiences but pose significant challenges of harassment. Common solutions, such as...

Challenges of Artificial Intelligence in Medicine.

Artificial Intelligence (AI) holds great promise for healthcare, promising improved patient outcomes and streamlining processes. Nevertheless, this tr...

Using C4.5 Algorithm to Gain Insights on Stakeholder Engagement and Use of Artificial Intelligence on Social Media in Dementia Caregiving Disparity Research.

We applied machine learning techniques to build models that predict perceived risks and benefits of using artificial intelligence (AI) algorithms to r...

Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models

Accurate medical symptom coding from unstructured clinical text, such as vaccine safety reports, is a critical task with applications in pharmacovig...

Robust Randomized Low-Rank Approximation with Row-Wise Outlier Detection

Robust low-rank approximation under row-wise adversarial corruption can be achieved with a single pass, randomized procedure that detects and remove...

UAC: Uncertainty-Aware Calibration of Neural Networks for Gesture Detection

Artificial intelligence has the potential to impact safety and efficiency in safety-critical domains such as construction, manufacturing, and health...

AI Hiring with LLMs: A Context-Aware and Explainable Multi-Agent Framework for Resume Screening

Resume screening is a critical yet time-intensive process in talent acquisition, requiring recruiters to analyze vast volume of job applications whi...

Data-Driven Safety Verification using Barrier Certificates and Matrix Zonotopes

Ensuring safety in cyber-physical systems (CPSs) is a critical challenge, especially when system models are difficult to obtain or cannot be fully t...

From Intuition to Understanding: Using AI Peers to Overcome Physics Misconceptions

Generative AI has the potential to transform personalization and accessibility of education. However, it raises serious concerns about accuracy and ...

AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference.

Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical...