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Diagnosing a patient from the early stages tremendously raises the chance of survival. Current clinical cancer detection approaches including X-ray, magnetic resonance imaging (MRI), and biomarker analysis not only fail to provide a precise border of the malignant tissue, especially in the early stages of cancer, but also can be invasive and lead to tissue damage. Recent progress in EM biosensor technologies has the potential to deliver a point-of-care diagnosis and surpass conventional methods regarding accuracy, time, and cost.", "keywords": ["Technology", "Organizations", "Science & Technology", "Sensors", "Tissue damage", "610", "Engineering", " Electrical & Electronic", "02 engineering and technology", "Cancer detection", "Costs", "Point of care", "ARRAYS", "3. 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Experimental results show the effectiveness of this method compared to the state of the art in the field.</p></article>", "keywords": ["Technology and Engineering", "Markov random field", "LORAKS", "Chemical technology", "TP1-1185", "02 engineering and technology", "image reconstruction", "Article", "NETWORKS", "magnetic resonance imaging; Markov random field; image reconstruction", "03 medical and health sciences", "0302 clinical medicine", "0202 electrical engineering", " electronic engineering", " information engineering", "magnetic resonance imaging", "MAGE-RECONSTRUCTION"]}, "links": [{"href": "http://www.mdpi.com/1424-8220/20/11/3185/pdf"}, {"href": "https://doi.org/1854/LU-8664006"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sensors", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-8664006", "name": "item", "description": "1854/LU-8664006", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8664006"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-06-03T00:00:00Z"}}, {"id": "20714903", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:18Z", "type": "Journal Article", "created": "2010-08-16", "title": "Infiltration of plasma rich in growth factors for osteoarthritis of the knee short-term effects on function and quality of life", "description": "Osteoarthritis (OA) is a highly prevalent, chronic, degenerative condition that generates a high expense. Alternative and co-adjuvant therapies to improve the quality of life and physical function of affected patients are currently being sought.A total of 808 patients with knee pathology were treated with PRGF (plasma rich in growth factors), 312 of them with OA of the knee (Outerbridge grades I-IV) and symptoms of >3\u00a0months duration met the inclusion criteria and were evaluated to obtain a sample of 261 patients, 109 women and 152 men, with an average age of 48.39. Three intra-articular injections of autologous PRGF were administered at 2-week intervals in outpatient surgery. The process of obtaining PRGF was carried out following the Anitua Technique. Participants were asked to fill out a questionnaire with personal data and the following assessment instruments: VAS, SF-36, WOMAC Index and Lequesne Index before the first infiltration of PRGF and 6\u00a0months after the last infiltration.Statistically significant differences (P\u00a0<\u00a00.0001) between pre-treatment and follow-up values were found for pain, stiffness and functional capacity in the WOMAC Index; pain and total score, distance and daily life activities in the Lequesne Index; the VAS pain score; and the SF-36 physical health domain. There were no adverse effects related to PRGF infiltration.At 6\u00a0months following intra-articular infiltration of PRGF in patients with OA of the knee, improvements in function and quality of life were documented by OA-specific and general clinical assessment instruments. These favourable findings point to consider PRGF as a therapy for OA.", "keywords": ["Male", "Platelet-Derived Growth Factor", "Platelet-Rich Plasma", "Recovery of Function", "Middle Aged", "Osteoarthritis", " Knee", "Magnetic Resonance Imaging", "Statistics", " Nonparametric", "Injections", " Intra-Articular", "3. Good health", "03 medical and health sciences", "0302 clinical medicine", "Surveys and Questionnaires", "Quality of Life", "Humans", "Female", "Longitudinal Studies", "Prospective Studies"]}, "links": [{"href": "https://doi.org/20714903"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Archives%20of%20Orthopaedic%20and%20Trauma%20Surgery", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20714903", "name": "item", "description": "20714903", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20714903"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-08-17T00:00:00Z"}}, {"id": "2750197518", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:31Z", "type": "Journal Article", "created": "2017-08-24", "title": "Sparse Recovery in Magnetic Resonance Imaging With a Markov Random Field Prior", "description": "Recent research in compressed sensing of magnetic resonance imaging (CS-MRI) emphasizes the importance of modeling structured sparsity, either in the acquisition or in the reconstruction stages. 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The results demonstrate an improved reconstruction performance compared with both the standard CS-MRI methods and the recent related methods.", "keywords": ["Mice", "Image Processing", " Computer-Assisted", "0202 electrical engineering", " electronic engineering", " information engineering", "Animals", "Brain", "Humans", "02 engineering and technology", "Magnetic Resonance Imaging", "Algorithms", "Markov Chains"]}, "links": [{"href": "http://xplorestaging.ieee.org/ielx7/42/8053927/08016375.pdf?arnumber=8016375"}, {"href": "https://doi.org/28858789"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/IEEE%20Transactions%20on%20Medical%20Imaging", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "28858789", "name": "item", "description": "28858789", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/28858789"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-01T00:00:00Z"}}, {"id": "f57c2c7f-f2fc-454d-a1d8-3f9dfe79e6ef", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[5.81, 47.26], [5.81, 54.76], [15.77, 54.76], [15.77, 47.26], [5.81, 47.26]]]}, "properties": {"themes": [{"concepts": [{"id": "farming"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "neural networks"}, {"id": "magnetic resonance imaging"}, {"id": "root architecture"}, {"id": "environmental modelling"}, {"id": "agriculture"}, {"id": "plant water relations"}, {"id": "hydraulic conductivity"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "opendata"}], "scheme": "Individual"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "non-geographic"}], "scheme": "individual"}], "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the BonaRes Module A-Project - BonaRes - Soil3's research activities.\" Although every care has been taken in preparing and testing the data, the BonaRes Module A-Project - BonaRes - Soil3 and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the BonaRes Module A-Project - BonaRes - Soil3 and the BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. 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