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Mismatch repair, p53, and L1 cell adhesion molecule status influence the response to chemotherapy in advanced and recurrent endometrial cancer.
BMC Cancer
December 2024
Department of Obstetrics and Gynecology, Institution of Women's Medical Life Science, Yonsei University College of Medicine, 50-1 Yonsei-Ro, Seodaemun-Gu, Seoul, 03722, Korea.
Objective: This study aimed to identify the recurrence and survival rates according to the mismatch repair (MMR), p53, and L1 cell adhesion molecule (L1CAM) status in patients with advanced and recurrent endometrial cancer (EC) receiving systemic chemotherapy.
Methods: This single-center retrospective cohort study included chemotherapy-naïve patients with advanced-stage (III/IV) or recurrent EC between January 2015 and June 2022 (n = 156), who were administered chemotherapy as adjuvant therapy or first-line palliative treatment. MMR and p53 status were assessed, and L1CAM was tested using immunohistochemistry in the p53-wild and MMR-proficient (p53wt/pMMR) group.
Faster and better than a physician?: Assessing diagnostic proficiency of ChatGPT in misdiagnosed individuals with neuromyelitis optica spectrum disorder.
J Neurol Sci
December 2024
The University of Texas Southwestern Medical Center, Department of Neurology, Neuroinnovation Program, Multiple Sclerosis & Neuroimmunology Imaging Program, Dallas, TX, USA; The University of Texas Southwestern Medical Center, Peter O'Donnell Jr. Brain Institute, Dallas, TX, USA. Electronic address:
Background: Neuromyelitis optica spectrum disorder (NMOSD) is a commonly misdiagnosed condition. Driven by cost-consciousness and technological fluency, distinct generations may gravitate towards healthcare alternatives, including artificial intelligence (AI) models, such as ChatGPT (Generative Pre-trained Transformer). Our objective was to evaluate the speed and accuracy of ChatGPT-3.
View Article and Find Full Text PDFEvaluating AI Capabilities in Bariatric Surgery: A Study on ChatGPT-4 and DALL·E 3's Recognition and Illustration Accuracy.
Obes Surg
December 2024
Minimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran.
Background: With the rise of artificial intelligence (AI) in medical education, tools like OpenAI's ChatGPT-4 and DALL·E 3 have potential applications in enhancing learning materials. This study aims to evaluate ChatGPT-4o's proficiency in recognizing bariatric surgical procedures from illustrations and assess DALL·E 3's effectiveness in generating accurate surgical illustrations.
Methods: Illustrations of six bariatric surgical procedures (One Anastomosis Gastric Bypass, Roux-en-Y Gastric Bypass, Single Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy, Sleeve Gastrectomy, Biliopancreatic Diversion, and Adjustable Gastric Banding) were sourced from the IFSO Atlas of Metabolic and Bariatric Surgery.
Enhance fashion classification of mosquito vector species via self-supervised vision transformer.
Sci Rep
December 2024
College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for efficiently addressing and enhancing control measures against mosquito-transmitted diseases.
View Article and Find Full Text PDFA quality control circle to improve preventive care for lower limb lymphedema in gynecologic oncology surgery.
Support Care Cancer
December 2024
Department of Gynecology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, 350001, China.
Objective: This study aims to enhance compliance with lower limb lymphedema (LLL) prevention care measures post-gynecologic oncology surgery (GOS) through quality control circle (QCC) activity, aiming to improve patient recovery outcomes and reduce postoperative complications.
Methods: A 6-month QCC activity was conducted within the hospital, employing the ten-step plan-do-check-act model for QCC activity. The root causes of inadequate implementation of LLL prevention care measures were analyzed, leading to the development of relevant strategies and protocols.
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