The application of artificial intelligence (AI) on prostate magnetic resonance imaging (MRI) has shown promising results. Several AI systems have been developed to automatically analyze prostate MRI for segmentation, cancer detection, and region of interest characterization, thereby assisting clinicians in their decision-making process. Deep learning, the current trend in imaging AI, has limitations including the lack of transparency "black box", large data processing, and excessive energy consumption. In this narrative review, the authors provide an overview of the recent advances in AI for prostate cancer diagnosis and introduce their next-generation AI model, Green Learning, as a promising solution.
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http://dx.doi.org/10.1016/j.ucl.2023.08.001 | DOI Listing |
Physiol Plant
January 2025
Laboratory of Biochemistry, Institut Químic de Sarrià, Universitat Ramon Llull, Barcelona, Spain.
Photosynthetic microalgae are promising green cell factories for the sustainable production of high-value chemicals and biopharmaceuticals. The chloroplast organelle is being developed as a chassis for synthetic biology as it contains its own genome (the plastome) and some interesting advantages, such as high recombinant protein titers and a diverse and dynamic metabolism. However, chloroplast engineering is currently hampered by the lack of standardized cloning tools and Design-Build-Test-Learn workflows to ease genomic and metabolic engineering.
View Article and Find Full Text PDFJ Chromatogr A
January 2025
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, PR China. Electronic address:
α-Terpineol and 1,8-cineole are two important compounds in essential oils. This study developed an efficient method to recover α-terpineol from model oil (MO) based on association extraction by in situ formations of deep eutectic solvent (DES) between α-terpineol and some quaternary ammonium salts (QASs) by hydrogen-bond (HB) interaction. Such interaction could be broken almost completely by the introduction of water, due to the stronger HB interaction between water and QASs, which could release α-terpineol by liquid-liquid separation and save the organic solvents consumption.
View Article and Find Full Text PDFSensors (Basel)
January 2025
United States Department of Agriculture-Agriculture Research Service, Grassland Soil and Water Research Laboratory, Temple, TX 76502, USA.
Efficient and reliable corn ( L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers. Unlike prior studies that focus mainly on county-level or controlled laboratory-scale areas, this study targets a production-scale area, better representing real-world agricultural conditions and offering more practical relevance for farmers.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Chair of Geoinformatics, Faculty of Geodesy, University of Zagreb, 10 000 Zagreb, Croatia.
Green infrastructure (GI) plays a crucial role in sustainable urban development, but effective mapping and analysis of such features requires a detailed understanding of the materials and state-of-the-art methods. This review presents the current landscape of green infrastructure mapping, focusing on the various sensors and image data, as well as the application of machine learning and deep learning techniques for classification or segmentation tasks. After finding articles with relevant keywords, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyzes) method was used as a general workflow, but some parts were automated (e.
View Article and Find Full Text PDFFoods
January 2025
Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, and Vascular Sciences, University of Padova, via Loredan, 18, 35121 Padova, Italy.
Foodborne illnesses represent a significant global health challenge, causing substantial morbidity and mortality. Conventional surveillance methods, such as laboratory-based reporting and physician notifications, often fail to enable early detection, prompting the exploration of innovative solutions. Social media platforms, combined with machine learning (ML), offer new opportunities for real-time monitoring and outbreak analysis.
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