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Titlebook: Advances in Intelligent Disease Diagnosis and Treatment; Research Papers in H Chee-Peng Lim,Ashlesha Vaidya,Lakhmi C. Jain Book 2024 The Ed

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21#
發(fā)表于 2025-3-25 05:32:49 | 只看該作者
22#
發(fā)表于 2025-3-25 08:26:19 | 只看該作者
Book 2024of a variety of AI and related methodologies to address specific medical challenges. From detecting pancreatic cancer, classifying micro-emboli in stroke diagnosis, to segmenting brain tumours from MRI data, and more, the culmination of these studies underscores the transformative impact AI and digi
23#
發(fā)表于 2025-3-25 14:23:49 | 只看該作者
1868-4394 ing populations using the recently evolved artificial intell.The book delves into innovations in AI and related computing paradigms for disease detection and diagnosis. The collected chapters elucidate the use of a variety of AI and related methodologies to address specific medical challenges. From
24#
發(fā)表于 2025-3-25 19:19:00 | 只看該作者
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發(fā)表于 2025-3-25 21:08:42 | 只看該作者
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發(fā)表于 2025-3-26 00:27:46 | 只看該作者
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發(fā)表于 2025-3-26 06:00:17 | 只看該作者
Boundary Detection of Incomplete Shapes in Breast Thermal Images Using Statistical Shape Modeling,ast in lateral left and right thermal images. This model is later used for the segmentation of the breast. The proposed technique effectively defined the organ‘s boundary using some manual landmarks. An automatic scheme defined the border of the breast as well. The proposed approach was successful in the segmentation of incomplete shapes, too.
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發(fā)表于 2025-3-26 11:43:48 | 只看該作者
29#
發(fā)表于 2025-3-26 15:00:27 | 只看該作者
Grundzüge der Finanzwissenschaft and late-stage detection. This chapter presents a novel approach for pancreatic cancer detection and classification using techniques such as single image super-resolution, image segmentation, image registration based on the region of interests, image fusion, and classification based on global shape
30#
發(fā)表于 2025-3-26 18:59:28 | 只看該作者
Die wohlfahrts?konomische Referenzweltg blood flow is performed by experts manually using a transcranial Doppler ultrasound device. However, correctly identifying microembolus signals over a long period of time is challenging. Therefore, an automatic microembolus-classification system that can have expert human labelling capabilities is
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