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21st IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2024

作者： Smeriglio, Riccardo Rosell-Mirmi, Joana Radeva, Petia Abante, Jordi Universitat de Barcelona Dpt. of Physics Spain Politecnico di Torino Control and Computer Engineering Dpt. Turin Italy Headache Research Group Vall d'Hebron Institut de Recerca Catalonia Barcelona Spain Universitat de Barcelona Institute of Neurosciences Dpt. of Mathematics & Computer Science Catalonia Barcelona Spain Laboratory of Stem Cells & Regenerative Medicine Creatio Production & Validation Center of Advanced Therapies Spain Universitat de Barcelona Institute of Neurosciences Dpt. of Biomedical Sciences Spain Dpt. of Mathematics & Computer Science Catalonia Barcelona Spain

ISBN: (纸本)9798350356632

Current genotype-to-phenotype models, such as polygenic risk scores, only account for linear relationships between genotype and phenotype and ignore epistatic interactions, limiting the complexity of the diseases that can be properly characterized. Protein-protein interaction networks have the potential to improve the performance of the models. Moreover, interactions at the protein level can have profound implications in understanding the genetic etiology of diseases and, in turn, for drug development. In this article, we propose a novel approach for phenotype prediction based on graph neural networks (GNNs) that naturally incorporates existing protein interaction networks into the model. As a result, our approach can naturally discover relevant epistatic interactions. We assess the potential of this approach using simulations and comparing it to linear and other non-linear approaches. We also study the performance of the proposed GNN-based methods in predicting Alzheimer's disease, one of the most complex neurodegenerative diseases, where our GNN approach outperform state of the art methods. In addition, we show that our proposal is able to discover critical interactions in the Alzheimer's disease. Our findings highlight the potential of GNNs in predicting phenotypes and discovering the underlying mechanisms of complex diseases. © 2024 IEEE.

关键词： Prediction models

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FraMark: A Blockchain Marketplace for a 5G Network Management using Fractional NFTs 7

FraMark: A Blockchain Marketplace for a 5G Network Managemen...

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7th World Symposium on Communication Engineering, WSCE 2024

作者： Michoulis, George Tsourdinis, Kyros Niotis, George Kyranou, Konstantinos Fountoukidis, Eleutherios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis Psannis, Konstantinos E. Goudos, Sotirios K. Sidroco Holdings Ltd R&D Dpt. Thessaloniki Greece Sidroco Holdings Ltd R&D Dpt. Nicosia Cyprus Democritus University of Thrace Dpt. of Computer Science Kavala Greece University of Western Macedonia Dpt. of Electrical & Computer Engineering Kozani Greece Kingston University London Kingston Upon Thames Dpt. of Networks and Digital Media Surrey United Kingdom University of Macedonia Department of Applied Informatics Thessaloniki Greece ELEDIA@AUTH School of Physics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9798331542825

This paper presents FraMark, a blockchain-based framework for 5G network management that utilizes Hyperledger Fabric and fractional Non-Fungible Tokens (NFTs) to optimize resource allocation. We introduce a comprehensive system that fractionalizes digital assets to represent 5G network resources, enhancing efficiency and allocation flexibility. Our framework addresses the challenges of 5G network management by ensuring low latency, high transaction throughput, and secure resource trading. We conduct experiments to evaluate the performance of our approach, including CPU and memory utilization, latency analysis, and block size assessment. The results demonstrate the effectiveness of FraMark in improving network resource utilization and transaction efficiency, validating our framework's claims. By leveraging blockchain technology and innovative resource slicing techniques, FraMark paves the way for dynamic and efficient 5G network management. © 2024 IEEE.

关键词： 5G mobile communication systems

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PURPLE: a PURPose-guided Log GEnerator (Extended Abstract) 4

PURPLE: a PURPose-guided Log GEnerator (Extended Abstract)

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Doctoral Consortium and the Tool Demonstration Track of the 4th International Conference on Process Mining, ICPM-D 2022

作者： Burattin, Andrea Re, Barbara Rossi, Lorenzo Tiezzi, Francesco Dpt. of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby Denmark School of Science and Technology University of Camerino Camerino Italy Dpt. of Statistica Informatica Applicazioni University of Florence Florence Italy

Process mining collects a variety of techniques. To test and compare these techniques, we need event logs tailored to their specific mining purposes, e.g., process discovery and conformance checking. To this aim, we propose the PURPLE tool, a generator of event logs supporting different mining purposes. PURPLE performs guided simulations of a business model, shaping the resulting event log by the selected mining purpose. © 2022 Copyright for this paper by its authors.

关键词： Data mining

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Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users

arXiv

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arXiv 2025年

作者： Rubio, José María Buades Moyà-Alcover, Gabriel Jaume-I-Capó, Antoni Petrović, Nataša UGiVIA Research Group University of the Balearic Islands Dpt. of Mathematics and Computer Science Palma07122 Spain University of the Balearic Islands Dpt. of Mathematics and Computer Science Palma07122 Spain

In this paper, we present a human-based computation approach for the analysis of peripheral blood smear (PBS) images images in patients with Sickle Cell Disease (SCD). We used the Mechanical Turk microtask market to crowdsource the labeling of PBS images. We then use the expert-tagged erythrocytesIDB dataset to assess the accuracy and reliability of our proposal. Our results showed that when a robust consensus is achieved among the Mechanical Turk workers, probability of error is very low, based on comparison with expert analysis. This suggests that our proposed approach can be used to annotate datasets of PBS images, which can then be used to train automated methods for the diagnosis of SCD. In future work, we plan to explore the potential integration of our findings with outcomes obtained through automated methodologies. This could lead to the development of more accurate and reliable methods for the diagnosis of SCD. © 2025, CC BY.

关键词： Crowdsourcing

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A comprehensive study on fidelity metrics for XAI

arXiv

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arXiv 2024年

作者： Miró-Nicolau, Miquel Jaume-I-Capó, Antoni Moyà-Alcover, Gabriel UGiVIA Research Group University of the Balearic Islands Dpt. of Mathematics and Computer Science Palma07122 Spain University of the Balearic Islands Dpt. of Mathematics and Computer Science Palma07122 Spain

The use of eXplainable Artificial Intelligence (XAI) systems has introduced a set of challenges that need resolution. Herein, we focus on how to correctly select an XAI method, an open questions within the field. The inherent difficulty of this task is due to the lack of a ground truth. Several authors have proposed metrics to approximate the fidelity of different XAI methods. These metrics lack verification and have concerning disagreements. In this study, we proposed a novel methodology to verify fidelity metrics, using a well-known transparent model, namely a decision tree. This model allowed us to obtain explanations with perfect fidelity. Our proposal constitutes the first objective benchmark for these metrics, facilitating a comparison of existing proposals, and surpassing existing methods. We applied our benchmark to assess the existing fidelity metrics in two different experiments, each using public datasets comprising 52,000 images. The images from these datasets had a size a 128 by 128 pixels and were synthetic data that simplified the training process. All metric values, indicated a lack of fidelity, with the best one showing a 30 % deviation from the expected values for perfect explanation. Our experimentation led us to conclude that the current fidelity metrics are not reliable enough to be used in real scenarios. From this finding, we deemed it necessary to development new metrics, to avoid the detected problems, and we recommend the usage of our proposal as a benchmark within the scientific community to address these limitations. © 2024, CC BY.

关键词： Decision trees

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META-EVALUATING STABILITY MEASURES: MAX-SENSTIVITY & AVG-SENSITIVITY

arXiv

引用

arXiv 2024年

作者： Miró-Nicolau, Miquel Jaume-I-Capó, Antoni Moyà-Alcover, Gabriel University of the Balearic Islands Dpt. of Mathematics and Computer Science Palma07122 Spain

The use of eXplainable Artificial Intelligence (XAI) systems has introduced a set of challenges that need resolution. The XAI robustness, or stability, has been one of the goals of the community from its beginning. Multiple authors have proposed evaluating this feature using objective evaluation measures. Nonetheless, many questions remain. With this work, we propose a novel approach to meta-evaluate these metrics, i.e. analyze the correctness of the evaluators. We propose two new tests that allowed us to evaluate two different stability measures: AVG-Sensitiviy and MAX-Senstivity. We tested their reliability in the presence of perfect and robust explanations, generated with a Decision Tree;as well as completely random explanations and prediction. The metrics results showed their incapacity of identify as erroneous the random explanations, highlighting their overall unreliability. © 2024, CC BY.

关键词： Decision trees

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Geometric-Based Nail Segmentation for Clinical Measurements

arXiv

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arXiv 2025年

作者： Galmés, Bernat Moyà-Alcover, Gabriel Bibiloni, Pedro Varona, Javier Jaume-I-Capó, Antoni University of the Balearic Islands Dpt. of Mathematics and Computer Science Palma07122 Spain Palma07010 Spain

We present a robust segmentation algorithm that can be used to obtain measurements of toe nails. The presented method assists in a medical study to objectively quantify the incidence of a specific pathology. Towards such assessment, we require a segmentation of the nail, which locally appears to be very similar to skin. Several algorithms are used, each of them leveraging a different aspect of the toenail appearance. We use the Hough transform to locate the tip of the toe and to estimate the nail location and size. Then, we classify the image’s super-pixels based on their geometry and photometric information. Afterwards, the watershed transform delineates the border of the nail. The method has been validated with a 348-image medical dataset, achieving an accuracy of 0.993 and an F-measure of 0.925. The method is robust across samples unalike in nail shape, skin pigmentation, illumination conditions and, more importantly, under the appearance of regions affected by a medical condition. © 2025, CC BY.

关键词： Image segmentation

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Electromigration Effects in Processes of Nano- Structured Thin Films Growth 12

Electromigration Effects in Processes of Nano- Structured Th...

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12th IEEE International Conference "Nanomaterials: Applications and Properties", NAP 2022

作者： Dvornichenko, Alina Kharchenko, Vasyl Kharchenko, Dmitrii Petrov, Serhii Sumy State University Dpt. Applied Mathematics And Modeling Of Complex Systems Sumy Ukraine Sumy State University Institute Of Applied Physics National Academy Of Sciences Of Ukraine Sumy Ukraine Institute Of Applied Physics National Academy Of Sciences Of Ukraine Sumy Ukraine Sumy State University Dpt. Computer Science Sumy Ukraine

ISBN: (数字)9781665489829

ISBN: (纸本)9781665489829

We discuss effects of electromigration in processes of nano-structured thin films growth at condensation from gaseous phase end epitaxial growth in the framework of numerical simulations. It will be shown that an increase in the strength of the electric field applied to the substrate promotes formation of percolate structures of adsorbate. We will analyze dynamics of the surface morphology change in details. This study provides insight into details of electromigration effects at self-organization of adatoms into percolating adsorbate islands during nano-structured thin films growth at both condensation from the gaseous phase and epitaxial growth of multi-layer pyramidal-like adsorbate structures. © 2022 IEEE.

关键词： Surface morphology

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Assessing Fidelity in XAI post-hoc techniques: A Comparative Study with Ground Truth Explanations Datasets

arXiv

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arXiv 2023年

The evaluation of the fidelity of eXplainable Artificial Intelligence (XAI) methods to their underlying models is a challenging task, primarily due to the absence of a ground truth for explanations. However, assessing fidelity is a necessary step for ensuring a correct XAI methodology. In this study, we conduct a fair and objective comparison of the current state-of-the-art XAI methods by introducing three novel image datasets with reliable ground truth for explanations. The primary objective of this comparison is to identify methods with low fidelity and eliminate them from further research, thereby promoting the development of more trustworthy and effective XAI techniques. Our results demonstrate that XAI methods based on the backpropagation of output information to input yield higher accuracy and reliability compared to methods relying on sensitivity analysis or Class Activation Maps (CAM). However, the backpropagation method tends to generate more noisy saliency maps. These findings have significant implications for the advancement of XAI methods, enabling the elimination of erroneous explanations and fostering the development of more robust and reliable XAI. © 2023, CC BY.

关键词： Sensitivity analysis

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A novel approach to generate datasets with XAI ground truth to evaluate image models

arXiv

引用

arXiv 2023年

With the increased usage of artificial intelligence (AI), it is imperative to understand how these models work internally. These needs have led to the development of a new field called eXplainable artificial intelligence (XAI). This field consists of on a set of techniques that allows us to theoretically determine the cause of the AI decisions. One main issue of XAI is how to verify the works on this field, taking into consideration the lack of ground truth (GT). In this study, we propose a new method to generate datasets with GT. We conducted a set of experiments that compared our GT with real model explanations and obtained excellent results confirming that our proposed method is correct. © 2023, CC BY.

关键词： Artificial intelligence

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