Titlebook: Applications of Medical Artificial Intelligence; Second International Shandong Wu,Behrouz Shabestari,Lei Xing Conference proceedings 2024 T

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/159499.jpg

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https://doi.org/10.1007/978-0-387-09437-3matoxylin-eosin (H &E) and immunohistochemistry (IHC) as relying solely on H &E can sometimes result in inaccurate cancer diagnoses. IHC examination offers additional evidence to support the diagnostic process. Given challenging accessibility issues of IHC examination, generating virtual IHC images

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Julien Matricon,Andrea Giuffrida PhD which pose requirements on the performance, robustness and complexity of computer-based analysis techniques. This paper poses the question whether Transformer-based architectures, which are capable to directly capture global contextual information, can handle the aforementioned endoscopic condition

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https://doi.org/10.1007/978-3-319-57371-7nificant role in clinical assessments to discriminate these neurological disorders from healthy controls, to grade disease severity, and to further differentiate dementia subtypes. In this paper, we propose a deep-learning based model specifically designed to evaluate gait impairment score for asses

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https://doi.org/10.1007/978-3-319-57371-7 As such, there has been immense research and progress on improving screening and clinical support for breast cancer. In this paper, we investigate enhancing clinical support for breast cancer with deep learning models using a newly introduced magnetic resonance imaging (MRI) modality called synthet