Artificial Intelligence II

Clinics in Dermatology, Journal Year: 2024, Volume and Issue: 42(5), P. 423 - 425

Published: June 27, 2024

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Artificial intelligence in cosmetic dermatology

Journal of Cosmetic Dermatology, Journal Year: 2024, Volume and Issue: 23(10), P. 3305 - 3311

Published: Aug. 27, 2024

Cosmetic dermatology is a growing field as more patients are seeking treatments for esthetic concerns. Traditionally, practitioners and utilize their own perceptions, current beauty standards, manual observation to determine satisfaction with cosmetic interventions. Artificial intelligence (AI) can be introduced into provide objective data-driven recommendations both dermatologists patients.

Language: Английский

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Quality of Information Provided by Artificial Intelligence Chatbots Surrounding the Management of Vestibular Schwannomas: A Comparative Analysis Between ChatGPT-4 and Claude 2

Otology & Neurotology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 4, 2025

Objective To examine the quality of information provided by artificial intelligence platforms ChatGPT-4 and Claude 2 surrounding management vestibular schwannomas. Study design Cross-sectional. Setting Skull base surgeons were involved from different centers countries. Intervention Thirty-six questions regarding schwannoma tested. Artificial responses subsequently evaluated 19 lateral skull using Quality Assessment Medical Intelligence (QAMAI) questionnaire, assessing “Accuracy,” “Clarity,” “Relevance,” “Completeness,” “Sources,” “Usefulness.” Main Outcome Measure The scores answers both chatbots collected analyzed Student t test. Analysis grouped stakeholders was performed with McNemar Stuart-Maxwell test used to compare reading level among chatbots. Intraclass correlation coefficient calculated. Results demonstrated significantly improved over in 14 36 (38.9%) questions, whereas higher-quality for only observed (5.6%) answers. Chatbots exhibited variation across dimensions “Usefulness,” demonstrating a statistically significant superior performance. However, no difference found assessment “Sources.” Additionally, at lower grade level. Conclusions failed consistently provide accurate schwannoma, although achieved higher most parameters. These findings demonstrate potential misinformation patients seeking through these platforms.

Language: Английский

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Comparative evaluation of artificial intelligence models GPT-4 and GPT-3.5 in clinical decision-making in sports surgery and physiotherapy: a cross-sectional study

BMC Medical Informatics and Decision Making, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 14, 2025

The integration of artificial intelligence (AI) in healthcare has rapidly expanded, particularly clinical decision-making. Large language models (LLMs) such as GPT-4 and GPT-3.5 have shown potential various medical applications, including diagnostics treatment planning. However, their efficacy specialized fields like sports surgery physiotherapy remains underexplored. This study aims to compare the performance decision-making within these domains using a structured assessment approach. cross-sectional included 56 professionals specializing physiotherapy. Participants evaluated 10 standardized scenarios generated by 5-point Likert scale. encompassed common musculoskeletal conditions, assessments focused on diagnostic accuracy, appropriateness, surgical technique detailing, rehabilitation plan suitability. Data were collected anonymously via Google Forms. Statistical analysis paired t-tests for direct model comparisons, one-way ANOVA assess across multiple criteria, Cronbach's alpha evaluate inter-rater reliability. significantly outperformed all criteria. Paired t-test results (t(55) = 10.45, p < 0.001) demonstrated that provided more accurate diagnoses, superior plans, detailed recommendations. confirmed higher suitability planning (F(1, 55) 35.22, protocols 32.10, 0.001). values indicated internal consistency (α 0.478) compared 0.234), reflecting reliable performance. demonstrates These findings suggest advanced AI can aid planning, strategies. should function decision-support tool rather than substitute expert judgment. Future studies explore into real-world workflows, validate larger datasets, additional beyond GPT series.

Language: Английский

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Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care

Cosmetics, Journal Year: 2024, Volume and Issue: 11(6), P. 206 - 206

Published: Nov. 26, 2024

Objectives: Artificial intelligence (AI) is transforming aesthetic dermatology, introducing new opportunities for personalized, predictive, and adaptive approaches in skin diagnostics, treatment planning, patient management. This review examines AI’s evolving role enhancing diagnostic precision, individualizing treatments, supporting dynamic care, with a focus on practical implementation clinical settings. Results: piece highlights how AI-based imaging predictive tools enable more precise diagnostics tailored protocols, leading to improved outcomes satisfaction. Some of the key benefits AI dermatology include ability detect subtle changes, simulate outcomes, adjust interventions real time. However, this manuscript also addresses significant challenges that practitioners face, such as technical constraints, data privacy concerns, algorithmic biases, financial barriers, which impact accessibility efficacy across diverse populations. Conclusions: While holds potential enhance its responsible integration requires addressing these through clinician training, ethical guidelines, robust security measures. Effective use will depend collaboration between technology developers, clinicians, regulatory bodies. Perspectives: Looking forward, development diverse, inclusive datasets transparent, patient-centered models be essential ensure reach all patients equitably safely. By prioritizing factors, AI-driven technologies would become reliable, accessible, transformative element practice.

Language: Английский

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Assessing the Impact of ChatGPT in Dermatology: A Comprehensive Rapid Review

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(19), P. 5909 - 5909

Published: Oct. 3, 2024

Background/Objectives: The use of artificial intelligence (AI) in dermatology is expanding rapidly, with ChatGPT, a large language model (LLM) from OpenAI, showing promise patient education, clinical decision-making, and teledermatology. Despite its potential, the ethical, clinical, practical implications application remain insufficiently explored. This study aims to evaluate effectiveness, challenges, future prospects ChatGPT dermatology, focusing on applications, interactions, medical writing. was selected due broad adoption, extensive validation, strong performance dermatology-related tasks. Methods: A thorough literature review conducted, publications related dermatology. search included articles English November 2022 August 2024, as this period captures most recent developments following launch 2022, ensuring that includes latest advancements discussions role Studies were chosen based their relevance ethical issues. Descriptive metrics, such average accuracy scores reliability percentages, used summarize characteristics, key findings analyzed. Results: has shown significant potential passing specialty exams providing reliable responses queries, especially for common dermatological conditions. However, it faces limitations diagnosing complex cases like cutaneous neoplasms, concerns about completeness information persist. Ethical issues, including data privacy, algorithmic bias, need transparent guidelines, identified critical challenges. Conclusions: While significantly enhance practice, particularly education teledermatology, integration must be cautious, addressing complementing, rather than replacing, dermatologist expertise. Future research should refine ChatGPT’s diagnostic capabilities, mitigate biases, develop comprehensive guidelines.

Language: Английский

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