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

松軟無力

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

癡呆

紅潤

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

效果

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

蚊帳

別名

Meditative

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

官僚統(tǒng)治

Benign

真繁榮

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.