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1. |
Record Nr. |
UNINA9910557435103321 |
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Autore |
Zhang Yudong |
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Titolo |
Deep Learning in Medical Image Analysis |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
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Descrizione fisica |
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1 online resource (458 p.) |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis. |
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2. |
Record Nr. |
UNINA9910557343403321 |
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Autore |
Guédron Stéphane |
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Titolo |
Mercury and Methylmercury Contamination of Terrestrial and Aquatic Ecosystems |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
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Descrizione fisica |
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1 online resource (152 p.) |
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Soggetti |
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Chemistry |
Research & information: general |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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This Special Issue aims to provide new insights into the issue of the mercury contamination of terrestrial and aquatic ecosystems. This ubiquitous contaminant has been used by humans for many years, resulting in global contamination. When this toxic contaminant is converted to methylmercury, it accumulates in trophic chains, which is a major issue for wildlife and human health. The nine articles contained within this Special Issue on ''Mercury and Methylmercury Contamination of Terrestrial and Aquatic Ecosystems'' endeavour to identify the historical evolution of Hg and MeHg levels in aquatic environments, and to evaluate the impact of current and historical human activities, such as mining, climate change, and soil erosion, on receptor ecosystems and food chains. |
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