Applications of ChatGPT in Otolaryngology–Head Neck Surgery: A State of the Art Review

Otolaryngology, Год журнала: 2024, Номер 171(3), С. 667 - 677

Опубликована: Май 8, 2024

To review the current literature on application, accuracy, and performance of Chatbot Generative Pre-Trained Transformer (ChatGPT) in Otolaryngology-Head Neck Surgery. PubMED, Cochrane Library, Scopus. A comprehensive applications ChatGPT otolaryngology was conducted according to Preferred Reporting Items for Systematic Reviews Meta-analyses statement. provides imperfect patient information or general knowledge related diseases found In clinical practice, despite suboptimal performance, studies reported that model is more accurate providing diagnoses, than suggesting most adequate additional examinations treatments vignettes real cases. has been used as an adjunct tool improve scientific reports (referencing, spelling correction), elaborate study protocols, take student resident exams reporting several levels accuracy. The stability responses throughout repeated questions appeared high but many some hallucination events, particularly references. date, are limited generating disease treatment information, improvement management lack comparison with other large language models main limitation research. Its ability analyze images not yet investigated although upper airway tract ear important step diagnosis common ear, nose, throat conditions. This may help otolaryngologists conceive new further

Язык: Английский

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Applications of Large Language Models in Pathology

Bioengineering, Год журнала: 2024, Номер 11(4), С. 342 - 342

Опубликована: Март 31, 2024

Large language models (LLMs) are transformer-based neural networks that can provide human-like responses to questions and instructions. LLMs generate educational material, summarize text, extract structured data from free create reports, write programs, potentially assist in case sign-out. combined with vision interpreting histopathology images. have immense potential transforming pathology practice education, but these not infallible, so any artificial intelligence generated content must be verified reputable sources. Caution exercised on how integrated into clinical practice, as produce hallucinations incorrect results, an over-reliance may lead de-skilling automation bias. This review paper provides a brief history of highlights several use cases for the field pathology.

Язык: Английский

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ChatGPT‐4 Consistency in Interpreting Laryngeal Clinical Images of Common Lesions and Disorders

Otolaryngology, Год журнала: 2024, Номер 171(4), С. 1106 - 1113

Опубликована: Июль 24, 2024

Abstract Objective To investigate the consistency of Chatbot Generative Pretrained Transformer (ChatGPT)‐4 in analysis clinical pictures common laryngological conditions. Study Design Prospective uncontrolled study. Setting Multicenter Methods Patient history and videolaryngostroboscopic images were presented to ChatGPT‐4 for differential diagnoses, management, treatment(s). responses assessed by 3 blinded laryngologists with artificial intelligence performance instrument (AIPI). The complexity cases between practitioners interpreting evaluated a 5‐point Likert Scale. intraclass correlation coefficient (ICC) was used measure strength interrater agreement. Results Forty patients mean score 2.60 ± 1.15. included. image interpretation 2.46 1.42. perfectly analyzed 6 (15%; 5/5), while GPT‐4 judges high 5 (12.5%; 4/5). Judges reported an ICC 0.965 ( P = .001). erroneously documented vocal fold irregularity (mass or lesion), glottic insufficiency, cord paralysis 21 (52.5%), 2 (0.05%), (12.5%) cases, respectively. indicated 153 63 additional examinations, respectively primary diagnosis correct 20.0% 25.0% cases. significantly associated AIPI r s 0.830; Conclusion is more efficient diagnosis, rather than analysis, selecting most adequate examinations treatments.

Язык: Английский

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Generative AI and Otolaryngology—Head & Neck Surgery

Otolaryngologic Clinics of North America, Год журнала: 2024, Номер 57(5), С. 753 - 765

Опубликована: Июнь 5, 2024

Язык: Английский

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Artificial Intelligence-Based Applications for Bone Fracture Detection Using Medical Images: A Systematic Review

Diagnostics, Год журнала: 2024, Номер 14(17), С. 1879 - 1879

Опубликована: Авг. 27, 2024

Artificial intelligence (AI) is making notable advancements in the medical field, particularly bone fracture detection. This systematic review compiles and assesses existing research on AI applications aimed at identifying fractures through imaging, encompassing studies from 2010 to 2023. It evaluates performance of various models, such as convolutional neural networks (CNNs), diagnosing fractures, highlighting their superior accuracy, sensitivity, specificity compared traditional diagnostic methods. Furthermore, explores integration advanced imaging techniques like 3D CT MRI with algorithms, which has led enhanced accuracy improved patient outcomes. The potential Generative Large Language Models (LLMs), OpenAI’s GPT, enhance processes synthetic data generation, comprehensive report creation, clinical scenario simulation also discussed. underscores transformative impact workflows care, while gaps suggesting future directions quality, model robustness, ethical considerations.

Язык: Английский

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Artificial intelligence driven real-time digital oral microscopy for early detection of oral cancer and potentially malignant disorders

Опубликована: Янв. 22, 2025

Confocal laser endomicroscopy (CLE) enables real-time diagnosis of oral cancer and potentially malignant disorders by in vivo microscopic tissue examination. One impediment to the widespread clinical adoption this technology is need for operator expertise image interpretation. Here we review application AI automatic classification CLE images discuss opportunities integrating advance digital pathology thus improving speed, precision reproducibility.

Язык: Английский

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Characterization of irradiated mucosa using confocal laser endomicroscopy in the upper aerodigestive tract

European Archives of Oto-Rhino-Laryngology, Год журнала: 2025, Номер unknown

Опубликована: Март 21, 2025

Язык: Английский

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A Systemic Review of Large Language Models and Their Implications in Dermatology

Australasian Journal of Dermatology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 6, 2025

ABSTRACT In computational linguistics, large language models have reached a significant turning point. They quickly spread throughout several sectors, including the medical field. By integrating demographics, clinical photos, interviews, or genetic data where appropriate, these technologies may offer deeper insights into patient in dermatology. also recommendations for suitable diagnosis and treatment. Their work dermatology influence education interactions with doctors by addressing patients' questions developing materials, addition to enhancing diagnostic procedures treatment schedule planning. Through thorough systematic evaluation of publicly accessible big model applications dermatology, paper seeks close current gap highlighting previously published research, identifying important obstacles, investigating potential future directions.

Язык: Английский

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ChatGPT in veterinary medicine: a practical guidance of generative artificial intelligence in clinics, education, and research.

arXiv (Cornell University), Год журнала: 2024, Номер 11, С. 1395934 - 1395934

Опубликована: Янв. 1, 2024

ChatGPT, the most accessible generative artificial intelligence (AI) tool, offers considerable potential for veterinary medicine, yet a dedicated review of its specific applications is lacking. This concisely synthesizes latest research and practical ChatGPT within clinical, educational, domains medicine. It intends to provide guidance actionable examples how AI can be directly utilized by professionals without programming background. For practitioners, extract patient data, generate progress notes, potentially assist in diagnosing complex cases. Veterinary educators create custom GPTs student support, while students utilize exam preparation. aid academic writing tasks research, but publishers have set requirements authors follow. Despite transformative potential, careful use essential avoid pitfalls like hallucination. addresses ethical considerations, provides learning resources, tangible guide responsible implementation. A table key takeaways was provided summarize this review. By highlighting benefits limitations, equips veterinarians, educators, researchers harness power effectively.

Язык: Английский

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Assessing the feasibility of ChatGPT-4o and Claude 3-Opus in thyroid nodule classification based on ultrasound images

Endocrine, Год журнала: 2024, Номер unknown

Опубликована: Окт. 11, 2024

Abstract Purpose Large language models (LLMs) are pivotal in artificial intelligence, demonstrating advanced capabilities natural understanding and multimodal interactions, with significant potential medical applications. This study explores the feasibility efficacy of LLMs, specifically ChatGPT-4o Claude 3-Opus, classifying thyroid nodules using ultrasound images. Methods included 112 patients a total 116 nodules, comprising 75 benign 41 malignant cases. Ultrasound images these were analyzed 3-Opus to diagnose or nature nodules. An independent evaluation by junior radiologist was also conducted. Diagnostic performance assessed Cohen’s Kappa receiver operating characteristic (ROC) curve analysis, referencing pathological diagnoses. Results demonstrated poor agreement results ( = 0.116), while showed even lower 0.034). The exhibited moderate 0.450). achieved an area under ROC (AUC) 57.0% (95% CI: 48.6–65.5%), slightly outperforming (AUC 52.0%, 95% 43.2–60.9%). In contrast, significantly higher AUC 72.4% 63.7–81.1%). unnecessary biopsy rates 41.4% for ChatGPT-4o, 43.1% 12.1% radiologist. Conclusion While LLMs such as show promise future applications imaging, their current use clinical diagnostics should be approached cautiously due limited accuracy.

Язык: Английский

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