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Titlebook: Artificial Intelligence Applications and Innovations; 20th IFIP WG 12.5 In Ilias Maglogiannis,Lazaros Iliadis,Antonios Papale Conference pr

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發(fā)表于 2025-3-25 04:47:13 | 只看該作者
22#
發(fā)表于 2025-3-25 09:53:42 | 只看該作者
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發(fā)表于 2025-3-25 15:38:17 | 只看該作者
A Novel Signature for Distinguishing Non-lesional from Lesional Skin of Atopic Dermatitis Based on aunderstood. As a result, current therapies do not always lead to satisfactory outcomes. Very few studies have addressed the potential use of transcriptomic data and machine learning algorithms in atopic dermatitis. In this paper, we present and detail the use of machine learning models over omics da
24#
發(fā)表于 2025-3-25 16:02:49 | 只看該作者
Advanced Mortality Prediction in?Adult ICU: Introducing a?Deep Learning Approach in?Healthcaredels that are essential in guiding clinical decision-making and resource allocation in critical care settings, such as Acute Physiology and Chronic Health Evaluation (APACHE) and Simplified Acute Physiology Score (SAPS), while effective, have limitations that restrain their adaptability and predicti
25#
發(fā)表于 2025-3-25 23:30:12 | 只看該作者
Advancing ScRNA-Seq Data Integration via?a?Novel Gene Selection Methodne, which aims at tailoring treatments to individuals’ genetic profiles. This study harnesses the power of single-cell RNA sequencing (scRNA-seq), a cutting-edge tool in next-generation sequencing, to delve into the transcriptomic intricacies of individual cells across diverse populations. Our metho
26#
發(fā)表于 2025-3-26 03:55:49 | 只看該作者
Data Augmentation Techniques for?Cross-Domain WiFi CSI-Based Human Activity Recognitioning in confined indoor environments. However, the strong environmental dependence inherent to CSI presents a challenge for robust cross-domain generalization, limiting its practical applicability. Drastic environmental variations, such as transitions between line-of-sight (LOS) and non-line-of-sight
27#
發(fā)表于 2025-3-26 07:55:38 | 只看該作者
28#
發(fā)表于 2025-3-26 08:43:09 | 只看該作者
Evaluation of Language Models for Multilabel Classification of Biomedical Textstion problems often involve the prediction of multiple labels simultaneously applying to a single instance. In this paper, we propose a structured approach for the implementation and evaluation of multilabel classification tasks in the context of biomedical texts. This involves selecting appropriate
29#
發(fā)表于 2025-3-26 13:46:48 | 只看該作者
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發(fā)表于 2025-3-26 17:02:35 | 只看該作者
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