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MRI-based deep learning radiomics to differentiate dual-phenotype hepatocellular carcinoma from HCC and intrahepatic cholangiocarcinoma: a multicenter study.
Insights Imaging
January 2025
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Objectives: To develop and validate radiomics and deep learning models based on contrast-enhanced MRI (CE-MRI) for differentiating dual-phenotype hepatocellular carcinoma (DPHCC) from HCC and intrahepatic cholangiocarcinoma (ICC).
Methods: Our study consisted of 381 patients from four centers with 138 HCCs, 122 DPHCCs, and 121 ICCs (244 for training and 62 for internal tests, centers 1 and 2; 75 for external tests, centers 3 and 4). Radiomics, deep transfer learning (DTL), and fusion models based on CE-MRI were established for differential diagnosis, respectively, and their diagnostic performances were compared using the confusion matrix and area under the receiver operating characteristic (ROC) curve (AUC).
Enhanced hybrid attention deep learning for avocado ripeness classification on resource constrained devices.
Sci Rep
January 2025
Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, 10300, Thailand.
Attention mechanisms such as the Convolutional Block Attention Module (CBAM) can help emphasize and refine the most relevant feature maps such as color, texture, spots, and wrinkle variations for the avocado ripeness classification. However, the CBAM lacks global context awareness, which may prevent it from capturing long-range dependencies or global patterns such as relationships between distant regions in the image. Further, more complex neural networks can improve model performance but at the cost of increasing the number of layers and train parameters, which may not be suitable for resource constrained devices.
View Article and Find Full Text PDFHigh-sensitivity flexible electrochemical sensor for real-time multi-analyte sweat analysis.
Talanta
January 2025
School of Material Science and Engineering, Shanghai University of Engineering Science, Shanghai, 201620, PR China. Electronic address:
Flexible sweat sensors play a crucial role in health monitoring and disease prevention by enabling real-time, non-invasive assessment of human physiological conditions. Sweat contains a variety of biomarkers, offering valuable insights into an individual's health status. In this study, we developed an advanced flexible electrochemical sensor featuring reduced graphene oxide (rGO)-based electrodes, modified with a composite material comprising nitrogen and sulfur co-doped holey graphene (HG) and MXene, with in-situ-grown TiO nanoparticles on the MXene.
View Article and Find Full Text PDFSpectrophotometric and computational characterization of charge transfer complex of selumetinib with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone and its utilization in developing an innovative green and high throughput microwell assay for analysis of bulk form and pharmaceutical formulation.
BMC Chem
January 2025
Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh, 11451, Saudi Arabia.
For paediatric patients suffering from neurofibromatosis, Selumetinib (SEL) is the only approved drug. Here an original ecofriendly and high pace method is introduced using 96- microwell spectrophotometric assay (MW-SPA) to measure SEL content in bulk and commercial pharmaceutical formulation (Koselugo capsules). This assay was relied on in-microwell formation of a coloured charge transfer complex (CTC) upon interaction of SEL with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ).
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