Data Mining Applications in Healthcare

Dear Colleagues,

Healthcare and life science is the most data-intensive industry in the world. Huge volumes of very heterogeneous raw data are generated daily by a variety of modern clinical information systems, such as Electronic Health Records (EHRs), Computerized Physician Order Entry (CPOE), Laboratory Information Systems, and Picture Archiving and Communications System (PACS). Medical sensors can generate unimaginable volumes of patient data per year. These information systems are utilized in many healthcare settings, such as physician offices and hospitals, and have been known for unlocking new sources of economic value, providing fresh insights into different science fields, and assisting in policy making.

Extracting useful knowledge from huge volumes of healthcare raw data (so-called data mining in healthcare) can be considered a processing pipeline that involves multiple distinct configuration stages to achieve full utilization. These stages include: data aggregation, data maintenance, data integration, data analytic, and pattern interpretation/application. Each stage faces several specific challenges.

The main objective of this Special Issue is to gather both researchers and practitioners to discuss technical and non-technical challenges, and explore previously unknown challenges and resolutions in discovering knowledge from healthcare data. Papers describing original research on both theoretical and practical aspects of data mining applications in healthcare are solicited.

Dr. Alex Kuo
Dr. Matteo Mantovani
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. Mathematics 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.

• healthcare data mining infrastructure, methodologies and tools
• healthcare data management/repositories
• standard development for healthcare data governance/interoperability
• metadata for healthcare data integration, discovery and interpretation
• visualization analytics for healthcare data
• healthcare data privacy/security
• real world healthcare data mining case study
• parallel and distributed healthcare data retrieval and analytics
• healthcare data availability, reliability and fault tolerance
• healthcare data-driven decision making and prescriptive analytics