Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe

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agitate

,Analysis and Interpretation of ECG Time Series Through Convolutional Neural Networks in Brugada Synexperimental assessments we use an original dataset of 306 ECGs collected from several clinical centers within the BrAID (Brugada syndrome and Artificial Intelligence applications to Diagnosis) project.

我吃花盘旋

Molecular Structure-Based Double-Central Drug-Drug Interaction Prediction,olecular Structure-based Double-Central Drug-Drug Interaction prediction(MSDC-DDI). MSDC-DDI utilizes a double-central encoder and a cross-dependent schema to generate the representations of the drugs. MSDC-DDI made effective and accurate predictions, which achieved up to more than 99% in DDI prediction.

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The Optimization and Parallelization of Two-Dimensional Zigzag Scanning on the Matrix,lts show that our proposed schemes perform well with large scales of matrices. Moreover, the design of parallel programming based on our proposed scheme has been given. Finally, we have discussed the efficiency of parallelization. The speedup we get is from 3.413 to 3.996, which is stably growth with the scales of matrices.

Precursor

Risk Stratification of Malignant Melanoma Using Neural Networks,ine learning methods, alterations of scanner-specific properties such as brightness, contrast or sharpness can have strong (negative) effects on the quality of the prediction methods, two ways to overcome this domain gap are discussed in this paper.

anniversary

0302-9743 n brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.  .978-3-031-44215-5978-3-031-44216-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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0302-9743 ne Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023..The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks i

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Artificial Neural Networks and Machine Learning – ICANN 2023978-3-031-44216-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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