ChatGPT-3.5 and ChatGPT-4 dermatological knowledge level based on the Specialty Certificate Examination in Dermatology

Summary: Natural Language Generation (NLG) has made significant progress in recent years, thanks to deep learning technologies like Transformer-based language models. This advancement has resulted in more fluent and coherent NLG, leading to improvements in tasks such as summarization, dialogue generation, and data-to-text conversion. However, deep learning-based generation is prone to producing unintended text, which affects system performance and fails to meet user expectations in real-world scenarios. To address this issue, researchers have conducted studies on measuring and mitigating hallucinated texts. This survey provides an overview of the research progress and challenges in the hallucination problem in NLG, covering metrics, mitigation methods, and task-specific research progress.

ACM COMPUTING SURVEYS (2023)

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Review Health Care Sciences & Services

ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns

Malik Sallam

Summary: ChatGPT is an AI-based conversational large language model with potential applications in health care education, research, and practice. A systematic review was conducted to investigate its utility and limitations. Benefits include improved writing, efficient analysis of datasets, streamlined workflow, and personalized learning, while concerns include ethical issues, plagiarism, limited knowledge, and cybersecurity risks.

HEALTHCARE (2023)

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Editorial Material Multidisciplinary Sciences

COULD AI HELP YOU TO WRITE YOUR NEXT PAPER?

Matthew Hutson

NATURE (2022)

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Article Dermatology

Artificial Intelligence in Dermatology: Challenges and Perspectives

Konstantinos Liopyris et al.

Summary: Artificial intelligence (AI) has great potential in dermatology, particularly in the early diagnosis and evaluation of skin cancer. Studies have shown that machine learning and convolutional neural networks can outperform or at least perform as well as clinicians in recognizing skin lesions. However, the application of AI algorithms in everyday clinical practice still faces challenges.

DERMATOLOGY AND THERAPY (2022)

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Article Computer Science, Artificial Intelligence

Human- versus Artificial Intelligence

J. E. (Hans) Korteling et al.

Summary: The paper discusses the similarities and differences between human and artificial intelligence, proposing three notions to provide more agreement and identify future research objectives. It also explores how to effectively utilize AI systems and capitalize on the strengths of human and artificial intelligence, emphasizing the need for an adequate mental model of AI mechanisms and intelligence awareness in humans. Additionally, the paper suggests a framework for educational content to achieve well-functioning human-AI systems.

FRONTIERS IN ARTIFICIAL INTELLIGENCE (2021)

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Review Dermatology