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Machine Learning Approaches for Biomedical Prediction

This special issue belongs to the section “Biomedical Engineering“.

Special Issue Information

Dear Colleagues,

This Special Issue titled "Machine Learning Approaches for Biomedical Prediction" aims to delve into the cutting-edge applications of machine learning within the realm of predicting and comprehending different biomedical phenomena. We invite scholarly contributions that span a broad spectrum of topics, ranging from the intricate nuances of predictive modeling for disease diagnosis, prognosis, and treatment response to the sophisticated integration of multi-modal biomedical data. Of particular significance is the emphasis on the transformative role played by innovative machine learning methodologies in propelling forward the domains of healthcare analytics, precision medicine, and telemedicine.

Furthermore, we extend an invitation to authors to present submissions that explore the intersection between machine learning and space exploration. This intriguing dimension seeks to stimulate insightful discussions on how these advanced technologies can significantly contribute to our understanding of health within the unique and challenging environment of space.

Dr. Antonio Pallotti
Dr. Noemi Scarpato
Dr. Alessandra Paffi
Dr. Antonello Rosato
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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

  • machine learning
  • biomedical prediction
  • predictive modeling
  • disease diagnosis
  • treatment response
  • biomedical data analysis
  • feature selection
  • precision medicine
  • healthcare analytics
  • computational biology
  • telemedicine
  • space exploration

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Appl. Sci. - ISSN 2076-3417