Machine Learning and AI Methods in Computer Vision and Visualization for Medical and Healthcare Applications

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: 30 June 2024 | Viewed by 176

Special Issue Editors

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Guest Editor
Department of Accounting and Information Systems, University of Canterbury, Christchurch 8041, New Zealand
Interests: AI-related areas; data analytics, business intelligence; web technology and application; e-learning; mobile learning; human–computer interaction; virtual reality; augmented reality

E-Mail Website
Guest Editor
School of Software Engineering, Dalian University, Dalian 116622, China
Interests: image processing; image fusion; image encryption; DNA computing; bioinformatics

Special Issue Information

Dear Colleagues,

Machine learning and relevant Artificial Intelligence (AI) methods have shown their capability and prevailed in many science and engineering fields including medicine and healthcare. Scientific visualisation in particular offers unrivalled methods for communicating various data elements. It broadly encompasses a number of significant areas of computer science research areas, such as visual computing, computer graphics, and computer vision. Machine learning algorithms are increasingly being used with visualisation and computer vision techniques as artificial intelligence advances. Because of the numerous non-intrusive, wearable, multi-modal, and sensor-based devices that are now possible thanks to technology, data gathered from healthcare-related activities and solutions serves as a good testing ground and playground for visualisations and computer vision techniques. These data typically bear certain distinctive qualities, such as having great practical value and being sensitive, complex, enormous in size, and multi-dimensional, which adds to the intrigue of the research investigation. The development of effective methods, applications, and even systems in healthcare is made possible by the integration of visualisation, computer vision, and machine learning.

Computer vision methods based on machine learning/AI have been developed for diagnosing tumours and nodules occurring in various human organs using image data acquired by different scanning modalities, e.g., CT and MRI. Some results are promising, but there is still room for improvement. It is often overlooked that machine learning/artificial intelligence techniques can be used for feature extraction and classification of non-image healthcare and medical data. These non-image data include text-based medical records, doctor's prescriptions, drug descriptions, diagnostic results, and more. This could be an important exploration of the possibilities of ML/AI. Visualization of non-image health data increases the utility of these data.

The Special Issue seeks to address the most recent developments in visualisation and computer vision employing machine learning and AI in the application area of medicine and healthcare, with a particular focus on healthcare data and its unsolved issues. The aim is to offer a thorough and up-to-date compilation of research and experiment efforts in the areas.

Dr. Pan Zheng
Dr. Shihua Zhou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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. Computers 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 1800 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.


  • visualization-based predictive analytics and therapy
  • medical image processing and computer vision
  • novel computer vision algorithms using healthcare data
  • machine-learning-enriched visualization methods
  • single and multi-dimensional medical image analysis
  • visualization of e-health data
  • cloud and big data visualization for healthcare
  • clinical/patient record visualization and analytics
  • patient behaviour data visualization and analysis
  • visualization and machine learning in Assistive Technology
  • visualization-aided diagnosis and prediction
  • symptoms-related patterns detection and recognition
  • visualization-guided medical procedures
  • medical data (image and non-image) feature extraction

Published Papers

This special issue is now open for submission.
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