New Sights of Deep Learning and Digital Model in Biomedicine
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 1265
Special Issue Editor
Interests: cardiovascular surgery; congenital heart disease; heart failure; myocardial metabolism
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleague,
This Special Issue explores the transformative impact of deep learning and digital modeling technologies within the field of biomedicine. As artificial intelligence continues to evolve, its applications in healthcare are becoming increasingly sophisticated, promising enhanced diagnostics, personalized treatment strategies, and improved patient outcomes.
It includes, but is not limited to, the following fields:
Deep learning algorithms: innovative approaches using neural networks and machine learning techniques tailored for medical imaging, genomics, and clinical data analysis.
Digital twins in healthcare: the application of digital twin technology to create virtual representations of patients or biological systems, enabling personalized medicine and real-time monitoring.
Predictive analytics: techniques for forecasting disease progression and treatment responses based on historical data, enhancing decision-making processes in clinical settings.
Integration with bioinformatics: utilization of deep learning in the processing of complex biological data, leading to advances in drug discovery and biomarker identification.
Ethics and regulation: considerations surrounding the ethical implications and regulatory challenges posed by the integration of AI in medicinal practices.
Interdisciplinary collaborations: the importance of cross-disciplinary teamwork involving data scientists, clinicians, and biomedical researchers to foster innovation in biomedicine.
The goal is to showcase cutting-edge research and emerging technologies that bridge deep learning and biomedicine.
It will inspire collaborations and dialog among researchers, healthcare professionals, and industry stakeholders.
This Special Issue aims to provide a comprehensive overview of current advancements and ongoing challenges in the application of deep learning and digital modeling in biomedicine, emphasizing the potential to revolutionize healthcare delivery and improve patient care.
Dr. John A. St. Cyr
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. Bioengineering is an international peer-reviewed open access monthly 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 2700 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
- deep learning
- digital model
- biomedicine
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