Advances in Disease Prediction

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 478

Special Issue Editors


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Guest Editor
School of Medicine, Istanbul Medipol University, Kavacık Mah. Ekinciler Cad. No.19, Kavacık Kavşağı, Beykoz, 34810 Istanbul, Turkey
Interests: epidemiology; health care management; social medicine; public health; healthcare policies; social determinants of health

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Guest Editor
Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
Interests: clinical epidemiology; chemotherapy and targeted therapy; surgery; gynecologic Oncology

Special Issue Information

Dear Colleagues,

In the era of digital health, complex and ubiquitous health data are collected from various sources, such as electronic health records, medical monitoring devices, wearable health systems, and mobile phone applications. Big data analytics techniques such as statistical analysis, machine learning, deep learning, generative intelligence, and digital twins can be applied to build innovative advances in disease prediction. Recently, the need for automated/intelligent laboratory recommendation systems has increased to provide more accurate and faster diagnoses. The fusion of various clinical data sources promoted by advances in laboratory approaches can significantly improve the diagnosis of diseases, illustrating how the digital revolution transforms clinical diagnostic practice. Based on concrete evidence, it is crucial and has a significant impact on the implementation of health care and programs. This fact highlights the important role of early diagnostics, including disease control, a range of treatment options, improved health services, improved health disparities and quality of life, etc. The aim of this Special Issue is to provide a comprehensive and current collection of state-of-the-art studies to advance disease prediction. Practical experience and experiments on the above-mentioned innovative analysis issues are also welcomed.

Prof. Dr. Chi-Chang Chang
Prof. Dr. Osman Hayran
Dr. Chalong Cheewakriangkrai
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. Diagnostics 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 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.

Keywords

  • early diagnostics
  • medical big data analytics
  • intelligent diagnostic models in public health
  • survival analysis and health hazard evaluations
  • machine learning and generative intelligence
  • intelligent digital twins
  • automated/intelligent laboratory recommendation systems

Published Papers

This special issue is now open for submission.
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