Medical Imaging and Machine Learning​

Dear Colleagues,

Machine learning refers to a set of techniques, mathematical models, and algorithms that allow computers to learn from data by first recognizing meaningful patterns in biomedical data, including images. It is a component of artificial intelligence because it facilitates the extraction of expressive patterns from data, which is a principle of human intelligence. In the past several decades, machine learning has shown itself as a complex tool and a solution assisting medical professionals in the diagnosis/prognosis of various cancers in different imaging modalities. Different machine learning methods are used in various medical fields, such as radiology, oncology, pathology, genetics, etc.

While much of the effort has so far been on introducing machine learning into the medical field, development of the present methods and algorithms in medicine also plays a significant role. Recently, deep neural network algorithms have significantly revolutionized conventional machine learning methods for a vast variety of applications, including medicine. Deep learning models increase the complexity of traditional algorithms while intensifying the dimensionality of data for detecting more details. This Special Issue will highlight advances in machine learning in cancer in all its diversity, covering both conventional and new deep learning methods in oncology.

Dr. Keyvan Farahani
Guest Editor
Dr. Bardia Yousefi
Co-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 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. Cancers 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 2900 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.