Machine Learning and Computing Techniques in Human Health

Dear Colleagues,

Nowadays, the idea of integrating clinical information with biomolecular data constitutes an indisputable trend given the growing and increasingly cheap data obtained from sequencing different types of molecules and the computational power of computer equipment. Such integration leads to better and earlier diagnostics, to accelerate the design of new drugs, and to improve the treatment of complex diseases such as cancer, hereditary conditions, rare diseases, metabolic disorders, and so on. In this context, the advent of technology has enormously enhanced the possibility of registration, use, and collection of many types of data related to human genomics, making possible the application of machine learning to address several problems in different areas related to human health.

This Special Issue is aimed at original papers describing recent advances where machine learning techniques intersect with health, healthcare, or life sciences. Sent articles must contain original content in theoretical analysis, methods, technical development, and/or novel health applications of machine learning techniques. Papers on the following topics are entirely aligned with the scope of this Special Issue:

• Computational aspects of human health diagnosis, prognosis, and treatment.
• Prediction of disease evolution with computer strategies.
• Development of computational methods for disease detection.
• Uses of machine learning methods to process gene expression data.
• Coupling of experimental and computational assays to identify novel gene signatures or marker genes.
• Identification of cross-links between human diseases and gene regulatory networks.
• Identification of the role of expressing specific genes or proteins in diseases.
• Use of explainable artificial intelligence for understand human health computational models.

Dr. Ignacio Ponzoni
Dr. Jessica Andrea Carballido
Dr. Rocío Luján Cecchini
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 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. Genes 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 2600 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.

• bioinformatics
• genome sequencing
• expression profiling
• histopathological bio-imaging
• image classification
• survival analysis
• cancer biomarkers
• drug design
• drug resistance
• stem cell treatments
• cell reprogramming
• artificial intelligence
• data analytics
• deep learning
• artificial neural networks
• evolutionary algorithms
• soft computing