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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

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Related Experiment Video

Updated: Jul 11, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Future Perspective of Risk Prediction in Aesthetic Surgery: Is Artificial Intelligence Reliable?

Alpay Duran, Oguz Cortuk, Bora Ok

    Aesthetic Surgery Journal
    |June 28, 2024
    PubMed
    Summary

    This study found that while informed consent forms offer the highest medical accuracy, large language models (LLMs) like ChatGPT-4 provide superior readability and clarity for patients seeking information on aesthetic surgery risks.

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    Area of Science:

    • Medical Informatics
    • Artificial Intelligence in Healthcare
    • Surgical Education

    Background:

    • Artificial intelligence (AI) shows significant promise in medicine, with rapid advancements indicating its future essential role in clinical practice.
    • Evaluating AI-generated medical information is crucial for safe patient communication.

    Purpose of the Study:

    • To compare the readability, clarity, and precision of medical knowledge from three large language models (LLMs) against informed consent forms.
    • To assess AI-generated content for 14 common aesthetic surgical procedures.

    Main Methods:

    • Systematic evaluation of ChatGPT-4, Gemini, and Copilot using 14 prompts on aesthetic procedure risks.
    • Comparison of LLM responses with risk sections from American Society of Plastic Surgeons (ASPS) informed consent forms.

    Main Results:

    • Informed consent forms showed highest medical knowledge accuracy, while LLM-generated content and informed consent forms scored highest for readability and clarity.
    • Procedure-specific informed consent forms, including LLM content, received the lowest medical knowledge accuracy scores.
    • Surgeons preferred ChatGPT-4 for patient materials due to perceived superior accuracy and information.

    Conclusions:

    • Physicians favor ChatGPT-4 for patient-facing materials due to its precise and comprehensive medical knowledge compared to other AI tools.
    • Adhering to ASPS recommendations for informed consent signing is vital to prevent complications and ensure adequate patient information.