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Artificial Intelligence: Advantages in Diagnostic Procedures
This special issue belongs to the section “Biomedical Engineering“.
Special Issue Information
Dear Colleagues,
Artificial intelligence is revolutionizing diagnostic procedures, enabling the production of faster, more accurate, and reproducible results across a wide range of medical fields. This Special Issue aims to highlight novel methodologies and AI applications in the diagnosis of complex, multifactorial diseases through advances in machine learning, deep learning, explainable AI, and GPT techniques. We welcome contributions that present innovations in clinical data analysis and discuss the integration of multimodal sources such as imaging, biosignals, genomics, and wearables to develop personalized diagnostics. This Special Issue emphasizes reproducibility, the ethical use of AI, and improvements in public health outcomes and seeks to explore new diagnostic frameworks, address current limitations in clinical practice, and propose cutting-edge solutions.
Dr. Carlos Eric Galván-Tejada
Dr. Irma Gonzalez-Curiel
Guest Editors
Manuscript Submission Information
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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
- artificial intelligence
- diagnostic systems
- machine learning
- deep learning
- biomedical signal processing
- medical imaging
- bioinformatics
- multimodal diagnostics
- clinical decision support systems
- personalized medicine
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