Data Science and Medical Informatics

Dear Colleagues,

With the explosion of data across domains—ranging from healthcare and finance to energy systems, education, manufacturing, and social networks—data science is redefining how organizations understand patterns, optimize operations, and make decisions. At its core, data science involves collecting, cleaning, analyzing, modeling, and interpreting complex and often high-dimensional data. This process requires not only technical skill but also domain-specific understanding, enabling insights that can directly inform policy, business strategy, scientific discovery, and public health. In particular, the healthcare industry has witnessed a surge in the adoption of data science methods to improve clinical decision-making, streamline hospital operations, and personalize patient care. As the volume and variety of health-related data grow—from electronic health records (EHRs) and wearable devices to imaging and genomics—data science is unlocking new frontiers in precision medicine and population health.

This Special Issue aims to explore the broad methodological landscape of data science while highlighting its transformative potential across both medical applications. We welcome contributions that showcase innovative data-driven approaches, either theoretical or applied, that address real-world challenges through intelligent analysis, predictive modeling, and system optimization. Topics of interest include, but are not limited to, the following:

• Machine learning and deep learning: algorithms for classification, regression, clustering, and anomaly detection across structured and unstructured data;
• Data mining and pattern discovery: techniques to extract hidden knowledge from large datasets, applicable in sectors such as healthcare, aerospace, social media, or cybersecurity;
• Data fusion and multimodal analysis: integrating diverse data sources—such as sensor networks, text, images, and signals—to form comprehensive analytical frameworks;
• Predictive analytics in clinical settings: forecasting disease progression, hospital readmissions, or treatment outcomes;
• Medical imaging and diagnostics: enhancing detection and diagnosis using computer vision and deep learning models;
• Personalized and precision medicine: tailoring treatment strategies based on individual genetic, behavioral, or environmental data;
• Healthcare operations and resource optimization: improving efficiency in hospital workflows, scheduling, and supply chain management;
• Remote monitoring and telehealth: Analyzing real-time data from wearables and IoT health devices to support chronic disease management and early intervention.

Original work highlighting the latest research and technical development is encouraged, but review papers and comparative studies are also welcome.

Prof. Dr. Junchang Xin
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. Applied Sciences 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 2400 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.

• data science
• machine learning
• statistical modeling
• predictive analytics
• optimization
• medical informatics
• natural language processing
• decision support
• explainable AI