Recent Advances in Artificial Intelligence and Bioinformatics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 2054

Special Issue Editor


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Guest Editor
Computer Science and Mathematics Department, University of Quebec at Chicoutimi, 555, Boulevard de l'Université, Chicoutimi, QC, Canada
Interests: design context-aware pervasive and intelligent architectural framework; smart systems; software engineering for smart systems; emerging architectures: Cloud, Fog, OpenFog, CoFog, Mobile Edge, Internet of Things
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Special Issue Information

Dear Colleagues,

The main purpose of the Applied Sciences MDPI journal is to provide insights into the use of artificial intelligence technologies in order to enhance innovations in bioinformatics systems and frameworks. The idea is to create awareness and experience about the past, current and prospects of artificial intelligence trends. In the literature, we call this phenomenon “artificial intelligence trends”; a field that needs the collaboration between experts in transdisciplinary domains to resolve several kinds of challenges. The researchers and practitioners were invited to do more collaborations to create economic and societal benefits with the integration and implementation of a large variety of artificial intelligence technologies and algorithms using the Internet of Things, smart Cloud Technologies, Virtual and Augmented reality, and Big Data.

This Special Issue aims to identify many problems in the emergent trends, and then gives and discusses many approaches to solve them. These approaches are described and discussed through received articles. The committee analyzed and evaluated many articles with peer review.

Topics of interest and included in this issue, but are not limited to:

Healthcare systems; artificial intelligence for monitoring systems; Internet of Things and artificial intelligence for bioinformatics; Machine learning and deep learning algorithms; enhanced deep learning algorithms; Explainable artificial intelligence algorithms; Big Data and artificial intelligence for bioinformatics; Telemedicine, smart software architecture for bioinformatics; Virtual Communities and Wellbeing; reliable mechanisms to improve the life quality of patients; Smart pervasive and ubiquitous health system; Cloud Computing.

Finally, the aim is to publish research contributions that significantly advance the state-of-the-art and trends research in the artificial intelligence area through many algorithms and technologies to improve the quality of modern and smart bioinformatics systems. It is our pleasure to announce that the editors of this edition are contributing to a Special Issue.

Prof. Dr. Hamid Mcheick
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • healthcare systems
  • artificial intelligence for monitoring systems
  • Internet of Things and artificial intelligence for bioinformatics
  • machine learning and deep learning
  • enhanced deep learning algorithms
  • explainable artificial intelligence algorithms
  • big data
  • cloud computing

Related Special Issue

Published Papers (1 paper)

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Review

33 pages, 1800 KiB  
Review
Better Safe Than Never: A Survey on Adversarial Machine Learning Applications towards IoT Environment
by Sarah Alkadi, Saad Al-Ahmadi and Mohamed Maher Ben Ismail
Appl. Sci. 2023, 13(10), 6001; https://doi.org/10.3390/app13106001 - 13 May 2023
Cited by 1 | Viewed by 1602
Abstract
Internet of Things (IoT) technologies serve as a backbone of cutting-edge intelligent systems. Machine Learning (ML) paradigms have been adopted within IoT environments to exploit their capabilities to mine complex patterns. Despite the reported promising results, ML-based solutions exhibit several security vulnerabilities and [...] Read more.
Internet of Things (IoT) technologies serve as a backbone of cutting-edge intelligent systems. Machine Learning (ML) paradigms have been adopted within IoT environments to exploit their capabilities to mine complex patterns. Despite the reported promising results, ML-based solutions exhibit several security vulnerabilities and threats. Specifically, Adversarial Machine Learning (AML) attacks can drastically impact the performance of ML models. It also represents a promising research field that typically promotes novel techniques to generate and/or defend against Adversarial Examples (AE) attacks. In this work, a comprehensive survey on AML attack and defense techniques is conducted for the years 2018–2022. The article investigates the employment of AML techniques to enhance intrusion detection performance within the IoT context. Additionally, it depicts relevant challenges that researchers aim to overcome to implement proper IoT-based security solutions. Thus, this survey aims to contribute to the literature by investigating the application of AML concepts within the IoT context. An extensive review of the current research trends of AML within IoT networks is presented. A conclusion is reached where several findings are reported including a shortage of defense mechanisms investigations, a lack of tailored IoT-based solutions, and the applicability of the existing mechanisms in both attack and defense scenarios. Full article
(This article belongs to the Special Issue Recent Advances in Artificial Intelligence and Bioinformatics)
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