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Titlebook: 8th International Conference on Advancements of Medicine and Health Care Through Technology; Proceedings of MEDIT Simona Vlad,Nicolae Mariu

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21#
發(fā)表于 2025-3-25 03:52:19 | 只看該作者
Conference proceedings 2024eld virtually on 20–22 October 2022, from Cluj-Napoca, Romania. It reports on both theoretical and practical developments in?biomedical imaging and image processing, health technology, technologies for education,? and biomedical signal processing and medical devices,?measurements and instrumentation
22#
發(fā)表于 2025-3-25 09:23:34 | 只看該作者
Conference proceedings 2024age processing, health technology, technologies for education,? and biomedical signal processing and medical devices,?measurements and instrumentation.? Both the conference and the realization of this book were supported by the Romanian National Society for Medical Engineering and Biological Technology?(SNIMTB)..
23#
發(fā)表于 2025-3-25 14:25:50 | 只看該作者
L?sungen zur vollst?ndigen Induktionce the data is processed it can be made available for querying in the beacon network for others for different purposes, among which are alleles of interest. To address machine learning necessities and the sharing of data through a beacon, BE-AI was developed.
24#
發(fā)表于 2025-3-25 19:31:46 | 只看該作者
25#
發(fā)表于 2025-3-25 21:31:06 | 只看該作者
3D-Druck für Schule und Hochschule (CNN), respectively of their combinations, to achieve an optimal classification accuracy. The considered CNNs were fused at classifier level, by employing various combination schemes, based on relevant feature selection, respectively on Kernel Principal Component Analysis (KPCA). At the end, a classification accuracy above 95% resulted.
26#
發(fā)表于 2025-3-26 02:19:49 | 只看該作者
27#
發(fā)表于 2025-3-26 06:53:13 | 只看該作者
Margret Liehn,Hannelore Schlautmannlude that data cleansing must be done before applying any machine learning algorithms, physicians should cope with the machine learning terminology and focus on understanding the models in use, and last but not least, the data cleansing should be driven by computer scientist though they have less understanding of the medical problem itself.
28#
發(fā)表于 2025-3-26 11:42:33 | 只看該作者
29#
發(fā)表于 2025-3-26 13:39:52 | 只看該作者
https://doi.org/10.1007/978-3-662-65190-2xNet, GoogleNet, InceptionV3 and Inception-ResNet-V2). Our paper also focuses on the challenges of obtaining a proper cataract detection system and proposes different approaches to improving its functionality.
30#
發(fā)表于 2025-3-26 18:03:01 | 只看該作者
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