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Open research questions in Artificial Intelligence in Healthcare and Education

2,044 unresolved questions extracted from the limitations and future-work sections of 4,279 Artificial Intelligence in Healthcare and Education papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • further study on the integration of AI in 6P medicine, - investigation of AI-driven approaches in the six domains of 6P medicine, - analysis of the impact of AI on patient outcomes and healthcare efficiency

    Artificial Intelligence For 6P Medicine: Consolidating AI Needs of Predictive, Preventive, Personalized, Participatory, Precision, and Public Health Trajectories · 2026 · DOI

  • Technical challenges in the implementation of AI in 6P medicine. Regulatory challenges in the integration of AI in healthcare. The need for standardized data and infrastructure to support AI adoption.

    Artificial Intelligence For 6P Medicine: Consolidating AI Needs of Predictive, Preventive, Personalized, Participatory, Precision, and Public Health Trajectories · 2026 · DOI

  • creating large cultivated and independent prospective data sets for LLM evaluation, - addressing the issue of data leakage or contamination, - further validation of the Weighted Matthews Correlation Coefficient

    LLM4SCREENLIT: Recommendations on assessing the performance of large language models for screening literature in systematic reviews · 2026 · DOI

  • The standard confusion-matrix metrics used to evaluate large language models can mislead under imbalanced conditions. There is a lack of consideration for the cost asymmetry of false negatives and false positives. The paper argues that there is a need for a more nuanced approach to evaluating LLM performance.

    LLM4SCREENLIT: Recommendations on assessing the performance of large language models for screening literature in systematic reviews · 2026 · DOI

  • current tools treat test executions as isolated events, lacking explicit aggregation mechanisms. current tools inadequately capture variability across model versions, configurations, and repeated runs. the need for viewing correctness as a distribution of outcomes rather than a binary property.

    Challenges in Testing Large Language Model-Based Software: A Faceted Taxonomy · 2026 · DOI

  • Future research might consider how students discursively construct this human-AI potentials across diverse educational contexts with statistical population sampling (Vicsek, 2010). Further research is needed in ethnographical contexts to enrich our understand- ing of ‘naturally occurring’ student discourse.

    Student conceptions of generative artificial intelligence in early adolescence · 2026 · DOI

  • The need to understand teachers' abilities and dispositions toward GenAI adoption. The gap between teachers' reported confidence in using GenAI and its actual integration into their practice.

    Readiness and adoption of generative AI in K-12 education: Perspectives from Australian teachers · 2026 · DOI

  • The study identifies the challenge of ensuring nurses' preparedness and perceptions regarding AI technologies in neonatal care. The integration of AI in healthcare poses challenges in terms of clinical decision-making, documentation, and workload pressures. The study highlights the need for strengthening NICU nurses' AI literacy and supporting their readiness to implement AI applications in practice.

    Artificial intelligence literacy and readiness among neonatal nurses: a structural equation modeling study · 2026 · DOI

  • The application of AI in neonatal care remains relatively unexplored. There is a need to understand nurses' preparedness and perceptions regarding AI technologies in neonatal care.

    Artificial intelligence literacy and readiness among neonatal nurses: a structural equation modeling study · 2026 · DOI

  • The study was conducted at a single tertiary oncology center. The sample size was limited to 400 participants. The study did not investigate the long-term effects of AI use. The study relied on self-reported data.

    The use of generative AI tools among individuals with cancer and their caregivers: a cross-sectional study of awareness, attitudes, and experiences · 2026 · DOI

  • Investigate the long-term effects of AI use on patient outcomes. Examine the impact of AI use on the physician-patient relationship. Develop strategies to increase AI adoption among patients and caregivers. Explore the use of AI in other clinical settings.

    The use of generative AI tools among individuals with cancer and their caregivers: a cross-sectional study of awareness, attitudes, and experiences · 2026 · DOI

  • Most commercial algorithms including artificial intelligence are proprietary - The paper did not address upskilling associated with the technology - Strategies to mitigate the deskilling impacts of the technology were not discussed

    Artificial intelligence and deskilling in medicine · 2026 · DOI

  • Investigation of the impact of artificial intelligence on physician deskilling - Study of the effects of artificial intelligence on clinical decision-making - Research on strategies to mitigate the deskilling impacts of artificial intelligence

    Artificial intelligence and deskilling in medicine · 2026 · DOI

  • real-world research including patients and real-life workflows, - interdisciplinary cooperation between technology developers and experienced physicians

    Artificial intelligence evolution in medicine · 2026 · DOI

  • The need for rigorous oversight and validation of agentic artificial intelligence in healthcare. The need for high-quality, representative data for training agentic artificial intelligence models. The need for interdisciplinary cooperation between technology developers and experienced physicians.

    Artificial intelligence evolution in medicine · 2026 · DOI

  • The incorporation of AI into medicine is still in its early stages, - Limited empirical research is available to confirm that such concerns exist and are valid, - Not every religious tradition has necessarily taken a stance on the wide range of issues surrounding this integration

    Religious Concerns about the Integration of Artificial Intelligence into Clinical Medicine and Patient Care · 2026 · DOI

  • Further research is needed to confirm the existence and validity of concerns surrounding AI integration into medicine, - Research should investigate how to address the limitations and potential biases of AI in spiritual care

    Religious Concerns about the Integration of Artificial Intelligence into Clinical Medicine and Patient Care · 2026 · DOI

  • The study used a purposive snowball recruitment strategy which may introduce sampling bias, - The study lacked specific guidelines for GenAI use at the time of data collection

    Assets and Threats of Generative AI in Higher Education: Exploring Chinese Postgraduate Students’ Perceptions · 2026 · DOI

  • Investigating the impact of GenAI on academic integrity, - Examining the effectiveness of structured GenAI instruction, - Exploring the use of GenAI in different academic disciplines

    Assets and Threats of Generative AI in Higher Education: Exploring Chinese Postgraduate Students’ Perceptions · 2026 · DOI

  • There remains a critical gap in systematic frameworks for prevention science applications. Almost none of the existing AI/ML suicide-risk models have been developed specifically for American Indian/Alaska Natives.

    Addressing Health Disparities through Community Engagement in Artificial Intelligence-Driven Prevention Science · 2026 · DOI

  • Investigating the effects of different AI collaboration approaches on learning gains, - Examining the impact of ChatGPT on creative problem-solving in various domains and populations

    Think First, ChatGPT Later: Guiding Human–AI Collaboration for Learning Gains in Independent Human Creativity · 2026 · DOI

  • The lack of understanding of the impact of ChatGPT on human creativity, particularly when its assistance is removed. The need for a novel approach to collaborating with ChatGPT that promotes learning gains in independent human creativity. The gap in prior research on the effect of ChatGPT on human cognition and learning.

    Think First, ChatGPT Later: Guiding Human–AI Collaboration for Learning Gains in Independent Human Creativity · 2026 · DOI

  • Further research is needed to explore the limitations and potential of using AI in analyzing textbook images, - Research should investigate the use of other AI models in analyzing textbook images, - Studies should examine the impact of AI-generated images on student learning outcomes

    Applying Artificial Intelligence in a Comparative Study of Science Images from Vietnamese and Taiwanese Textbooks · 2026 · DOI

  • There is a lack of understanding of the intentions of the curriculum in image design. There is a need to examine the efficiency of AI in analyzing science textbook images. There is a gap in the application of social semiotic theory in the analysis of science textbook images.

    Applying Artificial Intelligence in a Comparative Study of Science Images from Vietnamese and Taiwanese Textbooks · 2026 · DOI

  • The study identifies the challenge of ensuring that students remain aware of the extent to which generative AI shapes their own thinking. The experiment highlights the challenge of balancing the benefits of AI support with the need to cultivate independent reasoning and intellectual humility in students. The study notes the challenge of designing effective metacognitive reflection interventions to improve awareness of AI reliance.

    College students' metacognitive awareness of generative-AI reliance: an experimental study of decision confidence and attribution bias · 2026 · DOI

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2,044 open questions have been extracted from the limitations and future-work passages of 4,279 Artificial Intelligence in Healthcare and Education papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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