New Insights into Machine Learning and Biomedicine: Updates and Directions, 2nd Edition

Dear Colleagues,

The Special Issue "New Insights into Machine Learning and Biomedicine: Updates and Directions, 2nd Edition" aims to offer a current and in-depth perspective on the state of the art in machine learning and its biomedical applications. It encompasses recent developments and emerging trends in computational intelligence and machine learning methods applied to a range of biomedical challenges, including disease diagnosis, treatment planning, drug discovery, and medical image analysis.

This Special Issue primarily seeks to define and contextualize the role of machine learning in biomedicine. It explores the latest machine learning methodologies relevant to the healthcare sector and evaluates their real-world impacts on both patients and medical professionals. Additionally, it aims to highlight current research directions and outline potential future applications of machine learning in the biomedical field.

This Special Issue seeks to bring together researchers, practitioners, and domain experts to share their knowledge, experiences, and perspectives on the most recent advancements in this dynamic and rapidly evolving field. Contributions are welcome on a wide range of topics, including, but not limited to, the following:

• Machine learning algorithms and models for biomedical data analysis;
• Deep learning and neural networks in biomedical applications;
• Machine learning approaches in genomics and proteomics;
• Medical image analysis and computer vision techniques;
• Electronic health records and clinical decision support systems;
• Predictive modeling and precision medicine;
• Data integration and data mining in healthcare;
• Ethical, legal, and societal implications of machine learning in biomedicine;
• Integration of wearable device data into healthcare analytics;
• Cloud-based AI platforms for large-scale biomedical data processing;
• AI in public health surveillance and outbreak prediction.

The Special Issue also aims to explore future directions and key challenges in the field, emphasizing the transformative potential of machine learning in healthcare and its broader implications for society.

Dr. Cǎtǎlina Luca
Dr. Calin Corciova
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. 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.