The aim of this study was to determine the accuracy of medical staff assessment of trainees' operative competence. Over 18 months all 36 basic surgical trainees in SE Scotland were evaluated at the end of each attachment by consultants and registrars on their ability to perform key operative procedures using a previously validated assessment form. Frequency of assessment was compared with: (1) trainee's recording of whether the specific assessor had actually directly supervised them performing the procedure and (2) number of supervised procedures performed by trainees as determined by logbook data. A high percentage of both assessor groups provided assessment of procedures which they had not observed. Only 19/102 consultants and 20/95 registrars assessed only those procedures directly observed. A median of 9% (range 0-54%) of staff provided assessment for procedures that trainees had never even performed during that attachment. Such discrepancy needs to be addressed if accurate assessment of competence is to be achieved by trainers.
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http://dx.doi.org/10.1080/01421590500251175 | DOI Listing |
J Biophotonics
January 2025
Nanjing University of Chinese Medicine, Nanjing, China.
Liver malignancies, particularly hepatocellular carcinoma (HCC), pose a formidable global health challenge. Conventional diagnostic techniques frequently fall short in precision, especially at advanced HCC stages. In response, we have developed a novel diagnostic strategy that integrates hyperspectral imaging with deep learning.
View Article and Find Full Text PDFJ Adv Nurs
January 2025
College of Nursing, Guangzhou Medical University, Guangzhou, Guangdong, China.
Aims: To translate the Supportive and Palliative Care Indicators Tool (SPICT) into Chinese and conduct preliminarily tests of its performance in hospitalized patients with cancer.
Design: A cross-sectional validation study conducted from January to March 2024.
Methods: SPICT 2022 was translated in both directions, following the Brislin translation model, and the Chinese version culturally debugged through expert consultation and pre-testing.
J Dent Sci
January 2025
First Clinical Division, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, Beijing, China.
Background/purpose: Artificial intelligence (AI) can assist in medical diagnosis owing to its high accuracy and efficiency. This study aimed to develop a diagnostic system for automatically determining the degree of tooth wear (TW) using intraoral photographs with deep learning.
Materials And Methods: The study included 388 intraoral photographs.
J Dent Sci
January 2025
School of Dental Technology, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan.
Background/purpose: The performance of intraoral scanners (IOSs) relies on the operator's skills. However, whether operator experience influences IOS accuracy remains unclear. This study investigated the effect of operator experience on the trueness accuracy and time-based efficiency of IOSs.
View Article and Find Full Text PDFJ Dent Sci
January 2025
Division of Physiology, Department of Health Promotion, Kyushu Dental University, Kitakyushu, Japan.
Background/purpose: OpenAI's GPT-4V and Google's Gemini Pro, being Large Language Models (LLMs) equipped with image recognition capabilities, have the potential to be utilized in future medical diagnosis and treatment, ands serve as valuable educational support tools for students. This study compared and evaluated the image recognition capabilities of GPT-4V and Gemini Pro using questions from the Japanese National Dental Examination (JNDE) to investigate their potential as educational support tools.
Materials And Methods: We analyzed 160 questions from the 116th JNDE, administered in March 2023, using ChatGPT-4V, and Gemini Pro, which have image recognition functions.
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