Machine Learning Approaches for the Diagnosis of Sleep and Respiratory Disorders

Dear Colleagues,

We invite researchers and experts to submit their original research papers, review articles, and case studies for a Special Issue, entitled “Machine Learning Approaches for the Diagnosis of Sleep and Respiratory Disorders”, of the MDPI journal Diagnostics (ISSN 2075-4418, https://www.mdpi.com/journal/diagnostics).

This Special Issue will focus on the latest research advancements in the application of machine and deep learning techniques for the diagnosis, prediction, and phenotyping of sleep and respiratory disorders. The intricate link between sleep and respiration is well-established; conditions such as sleep apnea not only disrupt sleep but are also closely associated with respiratory diseases such as asthma, COPD, and bronchiectasis. Machine learning and deep learning offer unprecedented potential to unravel this complexity, enabling early detection and accurate diagnosis for a broad spectrum of conditions.

This Special Issue aims to showcase innovative research that leverages computational intelligence to address diagnostic challenges in both sleep and respiratory medicine. Topics of interest include, but are not limited to, the following:

Diagnosis and Prediction of Sleep and Respiratory Disorders:

Automated detection and classification of sleep apnea events and other sleep-related breathing disorders using polysomnography (PSG) or other signals;

Machine learning models for diagnosing, phenotyping, and predicting exacerbation risk in asthma, COPD, bronchiectasis, and other chronic respiratory diseases.

Advanced Data Analysis for Diagnosis:

Analysis of multi-modal data for diagnostic purposes, including polysomnography, actigraphy, medical imaging, pulmonary function tests, and data from wearable technologies;

Identification of novel diagnostic biomarkers and risk factors from large-scale clinical and demographic datasets.

Signal Processing and Novel Diagnostic Applications:

Automatic analysis of physiological signals (e.g., snoring sounds, oxygen saturation, respiratory effort, and cough sounds) for disorder detection and classification;

Development of accessible screening tools for high-risk populations (e.g., individuals with hypertension, diabetes, or cardiovascular disease).

Evaluation and Clinical Validation of Diagnostic Models:

Evaluation and comparison of different machine learning models for diagnostic applications;

Clinical studies and case reports validating the diagnostic accuracy and utility of AI models in sleep and respiratory medicine.

All submissions will be peer-reviewed. Accepted papers will be published in this Special Issue of Diagnostics, contributing to a growing body of knowledge at the intersection of AI and clinical medicine. Please ensure your submission conforms to the journal's guidelines and formatting requirements.

We look forward to receiving your contributions and advancing the diagnostic capabilities in sleep and respiratory medicine through the power of machine learning and deep learning.

Dr. Alaa Sheta
Dr. Shyam Subramanian
Dr. Salim R. Surani
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.

• diagnostics
• artificial intelligence
• sleep
• respiratory disorders
• healthcare