Titlebook: Data-Driven Clinical Decision-Making Using Deep Learning in Imaging; M. F. Mridha,Nilanjan Dey Book 2024 The Editor(s) (if applicable) and

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,Incorporating Residual Connections into a Multi-channel CNN for Lung Cancer Detection in Digital Pathe gradient problem, resulting in an optimized and efficient training process. Our proposed model outperformed all existing models including the SOTA model, with an accuracy of 89.95%, precision of 91.42%, recall of 88.84%, F1 of 89.68%, and specificity of 95.98%.

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Book 2024thodologies, and applications, providing readers with a comprehensive understanding of the field‘s current state and prospects. It begins with exploring domain adaptation in medical imaging and evaluating the effectiveness of transfer learning to overcome challenges associated with limited labeled d

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2197-6503 l machine learning models.Brings together a global network o.This book explores cutting-edge medical imaging advancements and their applications in clinical decision-making. The book contains various topics, methodologies, and applications, providing readers with a comprehensive understanding of the

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,Westindien und Mittelmeer 1871–74,stinct data distribution variations in each domain. This research delves into the effectiveness of transfer learning, specifically within the domain adaptation framework for medical imaging, addressing the challenges posed by varying data distributions across different medical domains. This paper us

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al decisions for patients and pathologists. Early diagnosis can help with prior treatment and reduce the mortality rate. In this research, we proposed a transfer learning (TL) approach fused with a squeeze-and-excitation (SE) attention mechanism to accurately diagnose brain tumours on a brain tumour

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Klaus Dieter Lorenzen,Wilfried Krokowskiion from large and complex medical image datasets. Currently, medical image datasets are increasing rapidly in size and complexity. Additionally, these algorithms are capable of processing and analyzing enormous amounts of data much more quickly and precisely than manual methods. However, it is chal

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Klaus Dieter Lorenzen,Wilfried Krokowski cancers is crucial for effective treatment planning and patient management. Leukemia and myeloma (plasma cell cancer), one types of malignancy that can damage the white blood cells (WBC) within the bone marrow. White blood cell identification, counting, and segmentation are crucial steps in effecti

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Der beleidigte gesunde Menschenverstand,ies, potentially leading to misdiagnosis and delayed treatment. Currently, doctors look at samples by hand or rely on confirmation tests that are not always easy to obtain, such as polymerase chain reaction (PCR) tests, which take a long time. A few studies have focused on individual disease classif