Publications by authors named "K D Kunze"
Background: Continued advancements in cartilage surgery and an accumulating body of evidence warrants a contemporary synthesis of return to sport (RTS) outcomes to provide updated prognostic data and to better understand treatment response.
Purpose: To perform an updated systematic review of RTS in athletes after knee cartilage restoration surgery.
Study Design: Systematic review; Level of evidence, 4.
Background: Failure of primary cartilage restoration procedures of the knee that proceed to necessitating revision cartilage procedures represent a challenging clinical scenario with variable outcomes reported in previous literature.
Purpose: To perform a systematic review and meta-analysis of clinical outcomes and adverse events after revision cartilage restoration procedures of the knee for failed primary cartilage procedures.
Study Design: Systematic review and meta-analysis; Level of evidence, 4.
Background: We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented kidney stone composition test system for potential improvements in test quality, efficiency, cost-effectiveness, and staff satisfaction.
Methods: We compared quality, efficiency, staff satisfaction, and financial data from the 6 months after the AI-augmented laboratory test system was deployed (test period) with data from the same 6-month period in the previous year (control period) to determine if AI-augmentation improved key performance indicators of this laboratory test.
Results: In the 6 months following the deployment (test period) of the AI-augmented kidney stone composition test system, 44 830 kidney stones were analyzed.
Large language models (LLMs) are generative artificial intelligence models that create content on the basis of the data on which it was trained. Processing capabilities have evolved from text only to being multimodal including text, images, audio, and video features. In health care settings, LLMs are being applied to several clinically important areas, including patient care and workflow efficiency, communications, hospital operations and data management, medical education, practice management, and health care research.
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- The study evaluated the accuracy and scope of medical information about total shoulder arthroplasty (TSA) provided by ChatGPT-4 compared to Google search results.
- Both platforms offered similar accuracy for FAQs requiring numerical answers, but ChatGPT-4 exclusively used academic sources while Google included various types of sources, such as medical practices and social media.
- The findings suggest that although both sources had comparable accuracy and clinical relevance, ChatGPT-4 mainly relied on trustworthy academic references, while Google’s information was more diverse and potentially less reliable.