Titlebook: Explainable Machine Learning for Multimedia Based Healthcare Applications; M. Shamim Hossain,Utku Kose,Deepak Gupta Book 2023 The Editor(s

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https://doi.org/10.1007/978-3-031-38036-5machine learning; deep learning; multimedia; artificial intelligence; interpretable machine learning; exp

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Mike Friedrichsen,Wolfgang Mühl-Benninghauss a tool in the analysis of medical images and videos, can facilitate the diagnosis process and contribute to increasing the accuracy in the decision-making stages of the experts. In addition, the evaluation of medical data, which requires experience and expertise, is achieved with the help of deep

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ements in data processing have made this process possible, and the advancement of technology for network infrastructures. In the healthcare systems, where data abundance has generated a rush of new techniques for effective data collection and processing, this new predicament is particularly noticeab

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Understanding Status as a Social Resources (DD), a malady that is frequent in dairy cattle and causes significant economic losses. For the purpose of the research, a member of the teaching staff who specialises in podiatry organised photographs of lesions caused by DD collected from 168 Holstein cows into groups based on the size of the le

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An Introduction to the Handbook, of information for cancer researchers. Machine learning models used in healthcare, like those used in other fields, are still mostly unknown. Understanding the rationale behind machine learning model predictions is critical in deciding trust if a clinician wants to initiate cancer treatment action

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Gordon Parker,Gemma L. Gladstoneng this malignancy early can save lives. More than 120 distinct tumors and related hereditary illnesses have individualized resources available, according to .. To diagnose breast cancer, machine learning techniques are mostly used. This research projects the use of eight machine learning (ML) appro