OralMLLM-Bench reveals performance gaps between multimodal large language models and clinicians on cognitive tasks for dental radiographic analysis across periapical, panoramic, and cephalometric images.
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AI co-clinician is a multimodal conversational AI that uses live audio-visual data for real-time medical reasoning in simulated telemedicine, approaching primary care physicians in management plans and differentials but lagging in physical exam and disease-specific tasks.
Imbalanced user-AI relationships form a distinct front-end ethical failure in healthcare AI that design choices such as restricted inputs and suppressed uncertainty can undermine agency and that reciprocity offers a path to more balanced interactions.
A narrative review of AI language technologies in multilingual healthcare identifies performance gaps in safety and equity and proposes seven grand challenges centered on reliability, human oversight, and cross-disciplinary collaboration.
citing papers explorer
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OralMLLM-Bench: Evaluating Cognitive Capabilities of Multimodal Large Language Models in Dental Practice
OralMLLM-Bench reveals performance gaps between multimodal large language models and clinicians on cognitive tasks for dental radiographic analysis across periapical, panoramic, and cephalometric images.
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Towards Conversational Medical AI with Eyes, Ears and a Voice
AI co-clinician is a multimodal conversational AI that uses live audio-visual data for real-time medical reasoning in simulated telemedicine, approaching primary care physicians in management plans and differentials but lagging in physical exam and disease-specific tasks.
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The Imbalanced User-AI Relationships as an Ethical Failure of Front-End Design in Healthcare AI
Imbalanced user-AI relationships form a distinct front-end ethical failure in healthcare AI that design choices such as restricted inputs and suppressed uncertainty can undermine agency and that reciprocity offers a path to more balanced interactions.
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Artificial intelligence language technologies in multilingual healthcare: Grand challenges ahead
A narrative review of AI language technologies in multilingual healthcare identifies performance gaps in safety and equity and proposes seven grand challenges centered on reliability, human oversight, and cross-disciplinary collaboration.