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J Hepatobiliary Pancreat Sci
January 2025
Department of Neonatal Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, China.
Background/purpose: Fetal hilar cyst is primarily diagnosed as two diseases after birth, cystic biliary atresia (CBA) and choledochal cyst (CC). The aim of our study was to explore more reliable indicators in early differential diagnosis of these cysts.
Methods: We recruited a total of 50 cases with a prenatal diagnosis of hepatic cyst at three centers, and patients were divided into a CBA group (n = 16) and CC group (n = 34) according to postnatal intraoperative diagnosis.
J Dent Sci
January 2025
Department of Oral Mucosal Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background/purpose: launched a call to action for dermatologists in the rise of syphilis. In practice, dermatologists and stomatologists perform early diagnoses of syphilis and refer patients to adequate treatment.
Materials And Methods: This scientometric study aimed to investigate and compare research trends and characteristics of syphilis publications by dermatologists and stomatologists in the Scopus database, with emphasis on the analysis of the keywords that can reflect research directions and topics of concern.
J Dent Sci
January 2025
Section of Oral and Maxillofacial Oncology, Division of Maxillofacial Diagnostic and Surgical Sciences, Faculty of Dental Science, Kyushu University, Fukuoka City, Fukuoka, Japan.
Background/purpose: Radiolucent lesions of the mandible, including ameloblastoma, odontogenic keratocyst (OKC), dentigerous cyst (DC) and simple bone cyst (SBC), are frequently encountered in clinical practice. However, they vary in type and occasionally in appearance. Each lesion needs a different treatment and approach; therefore, accurate diagnosis is crucial before treatment.
View Article and Find Full Text PDFJ Dent Sci
January 2025
School of Dentistry, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Background/purpose: Oral mucosal lesions are associated with a variety of pathological conditions. Most deep-learning-based convolutional neural network (CNN) systems for computer-aided diagnosis of oral lesions have typically concentrated on determining limited aspects of differential diagnosis. This study aimed to develop a CNN-based diagnostic model capable of classifying clinical photographs of oral ulcerative and associated lesions into five different diagnoses, thereby assisting clinicians in making accurate differential diagnoses.
View Article and Find Full Text PDFFront Cell Infect Microbiol
January 2025
Department of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People's Hospital, Hohhot, Inner Mongolia, China.
Introduction: This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis.
Methods: Proteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. Differential expression analysis was performed to identify proteins with altered expression, while Weighted Gene Co-expression Network Analysis (WGCNA) was applied to detect co-expression modules associated with clinical features of brucellosis.
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