Machine-Learning-Based Disease Diagnosis and Prediction

Dear Colleagues,

We are pleased to invite you to contribute to the Special Issue on ‘Machine-Learning-Based Disease Diagnosis and Prediction’ in Diagnostics. In recent years, the intersection of machine learning and healthcare has revolutionized disease diagnosis and prediction, presenting a promising frontier in medical research. This Special Issue aims to showcase the latest advancements, methodologies, and applications in leveraging machine learning techniques to enhance diagnostic accuracy and predict disease outcomes.

Machine learning algorithms have demonstrated remarkable efficacy in extracting meaningful patterns and insights from large-scale medical datasets, encompassing various modalities such as genomic, imaging, clinical, and wearable sensor data. By harnessing the power of artificial intelligence, researchers and clinicians can now decipher complex relationships between biomarkers, disease manifestations, and patient outcomes, leading to earlier detection, more accurate diagnosis, and personalized treatment strategies. The scope of this Special Issue encompasses a broad spectrum of research topics, including developing and validating machine learning models for disease classification, risk stratification, prognosis prediction, and treatment response assessment. We welcome original research articles, reviews, and methodological papers that explore innovative approaches, address key challenges, and contribute to advancing the field of machine-learning-based disease diagnosis and prediction.

This Special Issue aims to provide a platform for researchers and practitioners to share their latest findings, methodologies, and insights in machine-learning-based disease diagnosis and prediction. The subject matter of this Special Issue aligns with the scope of Diagnostics, which encompasses research on innovative diagnostic methods, tools, and technologies for various diseases. By fostering interdisciplinary collaboration and knowledge exchange, we aim at advancing the state of the art in disease diagnosis and prediction, ultimately contributing to improved patient outcomes and healthcare delivery.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Development and validation of machine learning models for disease diagnosis and prediction;
• Integration of multimodal data (e.g., imaging, genomic, and clinical) for enhanced diagnostic accuracy;
• Artificial intelligence in healthcare;
• Ethical and regulatory considerations in the deployment of machine learning for healthcare applications;
• Case studies and applications of machine learning in specific disease domains (e.g., cancer, cardiovascular diseases, and neurodegenerative disorders);
• Comparative studies and benchmarking of machine learning approaches for disease diagnosis and prediction;
• Healthcare analytics;
• Bioinformatics;
• Medical imaging analysis.

We look forward to receiving your contributions.

Dr. Fakhar Abbas
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 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.

• development and validation of machine learning models for disease diagnosis and prediction
• integration of multimodal data (e.g., imaging, genomic, and clinical) for enhanced diagnostic accuracy
• artificial intelligence in healthcare
• ethical and regulatory considerations in the deployment of machine learning for healthcare applications
• case studies and applications of machine learning in specific disease domains (e.g., cancer, cardiovascular diseases, and neurodegenerative disorders)
• comparative studies and benchmarking of machine learning approaches for disease diagnosis and prediction
• healthcare analytics
• bioinformatics
• medical imaging analysis