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The association between gestational selective serotonin reuptake inhibitor (SSRI) treatment and newborn thyroid screen: a large-scale cohort study.
BMC Pediatr
January 2025
Institute of Pediatric Endocrinology, Dana Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, 6 Weizmann Street, 6423906, Tel Aviv, Israel.
Background: The diagnosis of depression or anxiety treated by SSRIs has become relatively common in women of childbearing age. However, the impact of gestational SSRI treatment on newborn thyroid function is lacking. We explored the impact of gestational SSRI treatment on newborn thyroid function as measured by the National Newborn Screening (NBS) Program and identified contributory factors.
View Article and Find Full Text PDFThe value of MRI in differentiating ovarian clear cell carcinoma from other adnexal masses with O-RADS MRI scores of 4-5.
Insights Imaging
January 2025
Department of Radiology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Objective: To assess the utility of clinical and MRI features in distinguishing ovarian clear cell carcinoma (CCC) from adnexal masses with ovarian-adnexal reporting and data system (O-RADS) MRI scores of 4-5.
Methods: This retrospective study included 850 patients with indeterminate adnexal masses on ultrasound. Two radiologists evaluated all preoperative MRIs using the O-RADS MRI risk stratification system.
Simplified self-supervised learning for hybrid propagation graph-based recommendation.
Neural Netw
January 2025
School of Big Data & Software Engineering, Chongqing University, Chongqing, 401331, China. Electronic address:
Recent progress in Graph Convolutional Networks (GCNs) has facilitated their extensive application in recommendation, yielding notable performance gains. Nevertheless, existing GCN-based recommendation approaches are confronted with several challenges: (1) how to effectively leverage multi-order graph connectivity to derive meaningful node embeddings; (2) faced with sparse raw data, how to augment supervision signals without relying on auxiliary information; (3) given that GCNs necessitate the aggregation of neighborhood nodes, and the sparsity of these nodes can exacerbate the impact of noise data, how to mitigate the noise problem inherent in the raw data. For tackling aforementioned challenges, we devise a new hybrid propagation GCN-based method named S3HGN, incorporating a simplified self-supervised learning paradigm for recommendation.
View Article and Find Full Text PDFVirtual biopsy for non-invasive identification of follicular lymphoma histologic transformation using radiomics-based imaging biomarker from PET/CT.
BMC Med
January 2025
Department of Nuclear Medicine, West China Hospital, Sichuan University, Guoxue Alley, Address: No.37, Chengdu City, Sichuan, 610041, China.
Background: This study aimed to construct a radiomics-based imaging biomarker for the non-invasive identification of transformed follicular lymphoma (t-FL) using PET/CT images.
Methods: A total of 784 follicular lymphoma (FL), diffuse large B-cell lymphoma, and t-FL patients from 5 independent medical centers were included. The unsupervised EMFusion method was applied to fuse PET and CT images.
Mapping nutrient pollution in inland water bodies using multi-platform hyperspectral imagery and deep regression network.
J Hazard Mater
January 2025
Shanghai Municipal Institute of Surveying and Mapping, Shanghai, 200063, China.
Inland waters face multiple threats from human activities and natural factors, leading to frequent water quality issues, particularly the significant challenge of eutrophication. Hyperspectral remote sensing provides rich spectral information, enabling timely and accurate assessment of water quality status and trends. To address the challenge of inaccurate water quality mapping, we propose a novel deep learning framework for multi-parameter estimation from hyperspectral imagery.
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