“ChatGPT 4.0 Ghosted Us While Conducting Literature Search:” Modeling the Chatbot’s Generated Non-Existent References Using Regression Analysis

Internet Reference Services Quarterly, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 26

Published: Nov. 13, 2024

The integration of AI technologies like ChatGPT has transformed academic research, yet substantial gaps exist in understanding the implications AI-generated non-existent references literature searches. While prior studies have predominantly focused on medical and geography fields using descriptive statistics, a systematic investigation into 4.0's effectiveness generating accurate within realm science technology education remains unexplored, highlighting significant dearth research this critical area. This study, therefore, investigates reliability writing utilizing 4.0. Employing non-experimental correlational design, examines impact prompt specificity citation accuracy across various types prompts, including general, specific, methodological, review, interdisciplinary prompts. findings indicate that prompts correlate positively with references, while general frequently result references. Visualizations, confusion matrix precision-recall curve, illustrate model's performance. Ultimately, study underscores necessity well-structured to enhance reference quality cautions against AI-induced hallucinations produce which can significantly undermine credibility.

Language: Английский

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Assessing the Accuracy of Generative Conversational Artificial Intelligence in Debunking Sleep Health Myths: Mixed Methods Comparative Study With Expert Analysis

JMIR Formative Research, Journal Year: 2024, Volume and Issue: 8, P. e55762 - e55762

Published: March 14, 2024

Adequate sleep is essential for maintaining individual and public health, positively affecting cognition well-being, reducing chronic disease risks. It plays a significant role in driving the economy, safety, managing health care costs. Digital tools, including websites, trackers, apps, are key promoting education. Conversational artificial intelligence (AI) such as ChatGPT (OpenAI, Microsoft Corp) offers accessible, personalized advice on but raises concerns about potential misinformation. This underscores importance of ensuring that AI-driven information accurate, given its impact spread sleep-related myths.

Language: Английский

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Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions

Sensors, Journal Year: 2024, Volume and Issue: 24(22), P. 7126 - 7126

Published: Nov. 6, 2024

The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and policymakers about potential challenges integrating AI audiological practice. PubMed, Cochrane, Google Scholar databases were searched for articles published in English from 1990 2024 following query: "(audiology) AND ("artificial intelligence" OR "machine learning" "deep learning")". PRISMA extension scoping reviews (PRISMA-ScR) was followed. database research yielded 1359 results, selection process led inclusion 104 manuscripts. has evolved significantly over succeeding decades, 87.5% manuscripts last 4 years. Most types consistently used specific purposes, such as logistic regression other statistical machine learning tools (e.g., support vector machine, multilayer perceptron, random forest, deep belief network, decision tree, k-nearest neighbor, or LASSO) automated audiometry clinical predictions; convolutional neural networks radiological image analysis; large language models automatic generation diagnostic reports. Despite advances technologies, different ethical professional are still present, underscoring need larger, more diverse data collection bioethics studies field audiology.

Language: Английский

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Ethical dimensions of generative AI: a cross-domain analysis using machine learning structural topic modeling

International Journal of Ethics and Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Purpose The purpose of this study is to comprehensively examine the ethical implications surrounding generative artificial intelligence (AI). Design/methodology/approach Leveraging a novel methodological approach, curates corpus 364 documents from Scopus spanning 2022 2024. Using term frequency-inverse document frequency (TF-IDF) and structural topic modeling (STM), it quantitatively dissects thematic essence discourse in AI across diverse domains, including education, healthcare, businesses scientific research. Findings results reveal range concerns various sectors impacted by AI. In academia, primary focus on issues authenticity intellectual property, highlighting challenges AI-generated content maintaining academic integrity. healthcare sector, emphasis shifts medical decision-making patient privacy, reflecting about reliability security advice. also uncovers significant discussions educational financial settings, demonstrating broad impact societal professional practices. Research limitations/implications This provides foundation for crafting targeted guidelines regulations AI, informed systematic analysis using STM. It highlights need dynamic governance continual monitoring AI’s evolving landscape, offering model future research policymaking fields. Originality/value introduces unique combination TF-IDF STM analyze large corpus, new insights into multiple domains.

Language: Английский

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Generative AI and Otolaryngology—Head & Neck Surgery

Otolaryngologic Clinics of North America, Journal Year: 2024, Volume and Issue: 57(5), P. 753 - 765

Published: June 5, 2024

Language: Английский

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Assessing the diagnostic capacity of artificial intelligence chatbots for dysphonia types: Model development and validation

European Annals of Otorhinolaryngology Head and Neck Diseases, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Artificial intelligence optimizes the standardized diagnosis and treatment of chronic sinusitis

Frontiers in Physiology, Journal Year: 2025, Volume and Issue: 16

Published: March 13, 2025

Background Standardised management of chronic sinusitis (CRS) is a challenging but vital area research. Not only accurate diagnosis and individualised treatment plans required, post-treatment disease also indispensable. With the development artificial intelligence (AI), more “AI + medical” application models are emerging. Many AI-assisted systems have been applied to CRS, providing valuable solutions for clinical practice. Objective This study summarises research progress various focusing on their role in imaging pathological prognostic prediction treatment. Methods We used PubMed, Web Science, other Internet search engines with “artificial intelligence”、“machine learning” “chronic sinusitis” as keywords conduct literature studies from last 7 years. included eligible AI CRS our study, excluded outside this scope, categorized it according its diagnosis, treatment, prognosis prediction. provide an overview summary current advances optimize well difficulties challenges promoting standardization area. Results Through applications pathology personalised medicine prediction, can significantly reduce turnaround times, lower diagnostic costs accurately predict outcomes. However, number remain. These include lack product standards, standardised data, collaboration between different healthcare providers, non-interpretability systems. There may be data privacy issues involved. Therefore, improvements needed realise full potential CRS. Conclusion Our findings inform recommendations drive standardisation

Language: Английский

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Artificial Intelligence in Pediatric Otolaryngology: A State-of-the-Art Review of Opportunities and Pitfalls

International Journal of Pediatric Otorhinolaryngology, Journal Year: 2025, Volume and Issue: 194, P. 112369 - 112369

Published: May 4, 2025

Language: Английский

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Digital health technologies in swallowing care from screening to rehabilitation: A narrative review

Auris Nasus Larynx, Journal Year: 2025, Volume and Issue: 52(4), P. 319 - 326

Published: May 21, 2025

Language: Английский

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Investigating the role of artificial intelligence in predicting perceived dysphonia level

European Archives of Oto-Rhino-Laryngology, Journal Year: 2024, Volume and Issue: 281(11), P. 6093 - 6097

Published: Aug. 22, 2024

Language: Английский

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