Public Health & Policy

Clinical Trials

Latest AI and machine learning research in clinical trials for healthcare professionals.

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Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However, assessing the clinical efficacy of chemotherapy drugs remains a challenging task. In recent years, machine learning, especially artificial intelligence (AI), has emerged as a transformative tool in the field of oncology, capable of integrating multi...

Aug 15 2025 40355026

Ensuring SOTIF: Enhanced object detection techniques for autonomous driving.

Neural networks' insufficient interpretability can lead to unguaranteed Safety of the Intended Functionality (SOTIF) issues when perceptual results are not always met in autonomous driving applications. To address the safety shortcomings in the current object detection process, this study proposes an object detection algorithm to enhance the accuracy of the perception system's detection. We utiliz...

Aug 1 2025 40347558
Effect of Static vs. Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Controlled Trial

Large language model (LLM) chatbots show increasing promise in persuasive communication. Yet their real-world utility remains uncertain, particularl...

Adaptive Diffusion Denoised Smoothing : Certified Robustness via Randomized Smoothing with Differentially Private Guided Denoising Diffusion

We propose Adaptive Diffusion Denoised Smoothing, a method for certifying the predictions of a vision model against adversarial examples, while adap...

Efficient and Scalable Estimation of Distributional Treatment Effects with Multi-Task Neural Networks

We propose a novel multi-task neural network approach for estimating distributional treatment effects (DTE) in randomized experiments. While DTE pro...

Beyond the ATE: Interpretable Modelling of Treatment Effects over Dose and Time

The Average Treatment Effect (ATE) is a foundational metric in causal inference, widely used to assess intervention efficacy in randomized controlle...

Medical Red Teaming Protocol of Language Models: On the Importance of User Perspectives in Healthcare Settings

As the performance of large language models (LLMs) continues to advance, their adoption is expanding across a wide range of domains, including the m...

Medical Red Teaming Protocol of Language Models: On the Importance of User Perspectives in Healthcare Settings

As the performance of large language models (LLMs) continues to advance, their adoption is expanding across a wide range of domains, including the m...

ABCD: A Simulation Method for Accelerating Conversational Agents With Applications in Aphasia Therapy.

PURPOSE: Development of aphasia therapies is limited by clinician shortages, patient recruitment challenges, and funding constraints. To address these...

Jul 8 2025 40512969
Evaluating the Critical Risks of Amazon's Nova Premier under the Frontier Model Safety Framework

Nova Premier is Amazon's most capable multimodal foundation model and teacher for model distillation. It processes text, images, and video with a on...

Protocol for a multicenter randomized controlled trial to assess the usefulness of computer-aided detection systems for colonoscopy in colorectal cancer screening in the Asia-Pacific region (project CAD/NCCH2217).

Ensuring the high quality of colonoscopies in colorectal cancer (CRC) screening is essential to reducing CRC. Recently, computer-aided detection syste...

Jul 6 2025 40057966
Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data

Randomized trials are typically designed to detect average treatment effects but often lack the statistical power to uncover effect heterogeneity ov...

CPKD: Clinical Prior Knowledge-Constrained Diffusion Models for Surgical Phase Recognition in Endoscopic Submucosal Dissection

Gastrointestinal malignancies constitute a leading cause of cancer-related mortality worldwide, with advanced-stage prognosis remaining particularly...

Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke

Mechanical thrombectomy has become the standard of care in patients with stroke due to large vessel occlusion (LVO). However, only 50% of successful...

Detection of Rail Line Track and Human Beings Near the Track to Avoid Accidents

This paper presents an approach for rail line detection and the identification of human beings in proximity to the track, utilizing the YOLOv5 deep ...

SafePTR: Token-Level Jailbreak Defense in Multimodal LLMs via Prune-then-Restore Mechanism

By incorporating visual inputs, Multimodal Large Language Models (MLLMs) extend LLMs to support visual reasoning. However, this integration also int...

Truth, Trust, and Trouble: Medical AI on the Edge

Large Language Models (LLMs) hold significant promise for transforming digital health by enabling automated medical question answering. However, ens...

SAFER: Probing Safety in Reward Models with Sparse Autoencoder

Reinforcement learning from human feedback (RLHF) is a key paradigm for aligning large language models (LLMs) with human values, yet the reward mode...

Accelerated Value Iteration-Based Safe Q-Learning for Data-Driven Optimal Tracking Control.

In this article, an accelerated value iteration-based safe Q-learning (SQL) algorithm is developed to design the tracking controller for unknown nonli...

Jul 1 2025 40315067
ConsAMPHemo: A computational framework for predicting hemolysis of antimicrobial peptides based on machine learning approaches.

Many antimicrobial peptides (AMPs) function by disrupting the cell membranes of microbes. While this ability is crucial for their efficacy, it also ra...

Jul 1 2025 40519190
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