Latest AI and machine learning research in clinical trials for healthcare professionals.
Abstract Purpose: To quantify run-to-run reproducibility of Gemini 3 Flash Preview and GPT-5.2 for biomedical trial-success classification across temperature and reasoning/thinking settings, and to assess whether single-run reporting is sufficient. Methods: We utilized 250 randomized controlled oncology trial abstracts labeled POSITIVE/NEGATIVE based on primary endpoint success. With a fixed promp...
Dopamine (DA) has been implicated in exploration-exploitation behaviour, i.e., exploring novel, potentiallybetter options vs. exploiting known, previously rewarding options. Impairments in this trade-off occur inpsychiatric disorders involving DAergic dysfunction, including addiction and schizophrenia. Pharmacologicalstudies revealed a contribution of DA to exploration, but inconsistent findings s...
Robust safety of vision-language large models (VLLMs) under joint multilingual and multimodal inputs remains underexplored. Existing benchmarks are ty...
Vision-language models (VLMs) have become central to tasks such as visual question answering, image captioning, and text-to-image generation. However,...
Lysergic acid diethylamide (LSD) profoundly alters conscious experience, yet the electrophysiological mechanisms by which it reshapes neural dynamics ...
B cell-targeted therapies represent a transformative frontier for systemic lupus erythematosus (SLE) intervention, yet clinical recommendation of spec...
With the rapid development of industrial intelligence and unmanned inspection, reliable perception and safety assessment for AI systems in complex and...
Meta reinforcement learning (RL) allows agents to leverage experience across a distribution of tasks on which the agent can train at will, enabling fa...
The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current guard...
Patient selection and enrolment into phase III randomized clinical trials (RCTs) of adjuvant cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor therap...
The rapid advancement of Multimodal Large Language Models (MLLMs) has introduced complex security challenges, particularly at the intersection of text...
Importance: Emerging evidence suggests healthcare AI systems may exhibit deceptive alignment (appearing safe during validation while optimizing for mi...
As Multimodal Large Language Models (MLLMs) acquire stronger reasoning capabilities to handle complex, multi-image instructions, this advancement may ...
Background and Aims: Pragmatic clinical trials are designed to assess interventions in real-world settings, and their broad inclusion criteria and cli...
In this paper, the CD-TWINSAFE is introduced, a V2I-based digital twin for Autonomous Vehicles. The proposed architecture is composed of two stacks ru...
The rapid integration of AI algorithms in safety-critical applications such as autonomous driving and healthcare is raising significant concerns about...
Background/ObjectivesHead and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surger...
The rapid evolution of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) has driven major gains in reasoning, perception, and ...
Sustainability is becoming increasingly critical in the maritime transport, encompassing both environmental and social impacts, such as Greenhouse Gas...
ObjectiveLarge language models (LLMs) are increasingly embedded in mental-health chatbots, yet safe deployment is limited by two unresolved challenges...