Research (8)
Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy
Generative artificial intelligence (GAI) advancements have ignited new expectations for artificial intelligence (AI)-enabled educational transformations. Based on the theory of planned behavior (TPB), this study combines structural equation modeling and interviews to analyze the influencing factors of Chinese university students’ GAI technology usage intention. Regarding AI literacy, students’ cognitive literacy in AI ethics scored the highest (M = 5.740), while AI awareness literacy scored the
The Opportunities and Risks of Large Language Models in Mental Health
Unlabelled: Global rates of mental health concerns are rising, and there is increasing realization that existing models of mental health care will not adequately expand to meet the demand. With the emergence of large language models (LLMs) has come great optimism regarding their promise to create novel, large-scale solutions to support mental health. Despite their nascence, LLMs have already been applied to mental health-related tasks. In this paper, we summarize the extant literature on efforts
Integrated image-based deep learning and language models for primary diabetes care
Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM
Generative AI enhances individual creativity but reduces the collective diversity of novel content
Creativity is core to being human. Generative artificial intelligence (AI)-including powerful large language models (LLMs)-holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on generative AI ideas. We study the causal impact of generative AI ideas on the production of short stories in an online experiment where some writers obtained story ideas from an LLM. We find that access to generative AI ideas causes stories to be evaluated as more creative, b
The ethics of ChatGPT in medicine and healthcare: a systematic review on Large Language Models (LLMs)
With the introduction of ChatGPT, Large Language Models (LLMs) have received enormous attention in healthcare. Despite potential benefits, researchers have underscored various ethical implications. While individual instances have garnered attention, a systematic and comprehensive overview of practical applications currently researched and ethical issues connected to them is lacking. Against this background, this work maps the ethical landscape surrounding the current deployment of LLMs in medici
Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells
The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed.
Evaluation and mitigation of the limitations of large language models in clinical decision-making
Clinical decision-making is one of the most impactful parts of a physician's responsibilities and stands to benefit greatly from artificial intelligence solutions and large language models (LLMs) in particular. However, while LLMs have achieved excellent performance on medical licensing exams, these tests fail to assess many skills necessary for deployment in a realistic clinical decision-making environment, including gathering information, adhering to guidelines, and integrating into clinical w
Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making
The rapid integration of artificial intelligence (AI) systems into various domains has raised concerns about their impact on individual and societal wellbeing, particularly due to the lack of transparency and accountability in their decision-making processes. This review aims to provide an overview of the key legal and ethical challenges associated with implementing transparency and accountability in AI systems. The review identifies four main thematic areas: technical approaches, legal and regu