Titlebook: Explainable Machine Learning in Medicine; Karol Przystalski,Rohit M. Thanki Book 2024 The Editor(s) (if applicable) and The Author(s), und

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Critique as a Notion of Spiritualityscan, we receive a set of images, but the set is a capture of a small piece (slice) of our body. It is even possible to combine the MRI slices into a 3D model as the distance between the slices is fixed. A different approach is proposed in videos, such as ultrasound videos, in which we see changes i

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Karol Przystalski,Rohit M. ThankiProvides a primer on explainable artificial intelligence and machine learning methods that can be used in medical cases.Presents how explainable AI aids in choosing ML algorithms that give better perf

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Synthesis Lectures on Engineering, Science, and Technologyhttp://image.papertrans.cn/e/image/319300.jpg

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Meditative

https://doi.org/10.1007/978-3-031-44877-5Explainable Machine Learning; Medical Machine Learning; Medicine Artificial Intelligence; Medical Data

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Benign

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Mathematics and Its Applicationsigence (XAI) and its applications in the medical domain. This book provides a thorough exploration of the challenges and opportunities that arise when integrating machine-learning models into medical decision-making processes.