This study compares students' evaluation of a traditional and an innovative undergraduate family medicine (FM) courses. The old curriculum was traditional and teacher-centered. Changes in-line with the innovative learning concepts were introduced. While innovative course (IC) students had significant improvement in both their attitude towards innovative learning methods and self-assessment of knowledge, traditional course students had improvement only in self-assessment of knowledge. Students in both courses did not show post-cycle improvement in perception of their own skills and were dissatisfied with the Health Center (HC) tutors' training. The need to recruit trained family physicians at the affiliated HC became evident. IC students valued the exercise of adding their generated learning needs as part of the curriculum. Other lessons learned were presented. We hope that findings of this study would encourage medical colleges in the region to critically review their FM courses.
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http://dx.doi.org/10.1080/13576280050074507 | DOI Listing |
J Hosp Med
January 2025
Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
Dizziness is a common clinical presentation that incurs huge financial costs. It is frequently misdiagnosed due to a wide differential involving both benign (inner ear disease) and serious (stroke) disorders. Traditional frameworks that emphasize symptom quality (dizziness/lightheadedness/vertigo) lack diagnostic utility.
View Article and Find Full Text PDFJ Orthop Surg Res
January 2025
Department of Rehabilitation, The Affiliated Hospital of Youjiang Medical University for Nationalities, No.18, Zhongshan 2nd Road, Baise, 533000, Guangxi Zhuang Autonomous Region, China.
Background: Osteoporosis (OP) frequently occurs in post-menopausal women, increasing the risk of fracture. Early screening OP could improve the prevention of fractures.This study focused on the significance of miR-208a-3p in diagnosing OP and development regulation, aiming to explore a novel biomarker and therapeutic target for OP.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, 510515, China.
Background: Radix Fici Hirtae, the dry root of Ficus hirta, is a famous ethnomedicine and food that has been widely used by Yao and Zhuang nationalities in southern China for its potent antitumor, antifungal, and hepatoprotective effects. Recently, owing to over-exploitation and habitat destruction, F. hirta has been pushed to the brink of depletion.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Center for Plastic & Reconstructive Surgery, Department of Stomatology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Background: The purpose of this study was to evaluate the validity of near-infrared light reflection for detecting different depths of proximal caries in posterior teeth and to compare it with commonly used clinical oral examinations and bitewing radiography images.
Methods: Twenty-six patients with a total of 516 proximal surfaces were included in this study. The ground truth of the proximal caries was determined through a consensus reached by two experienced dentists after an intraoral examination assisted by bitewing radiographs.
Eur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
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