Applications of Big Data Mining in Healthcare
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Care Sciences".
Deadline for manuscript submissions: closed (15 May 2024) | Viewed by 486
Special Issue Editors
Interests: data mining; machine learning; natural language processing
Special Issue Information
Dear Colleagues,
Rapidly growing healthcare data have encompassed multiple scales ranging from individuals to populations and have connected multiple sources of the healthcare system, such as clinical records, guidelines, and patient-provided data obtained during diagnosis, prognosis, treatment and postoperative follow-up. These data are becoming a valuable resource for improving clinical activity with technology and bridging the gap between AI research and clinical applications. Meanwhile, the extraction and understanding of vast amounts of large, noisy and complex medical data create substantial barriers to the translation of routinely collected data into knowledge that drives the continual improvement of clinical solutions.
For medical informatics needs, AI technologies including computer vision, natural language processing, machine learning, data mining, and knowledge representation have recently made significant advances in processing medical and healthcare vision or text data and enabling decision makers to better interpret and utilize data. In particular, deep learning often results in automated feature discovery from data, and it has demonstrated impressive performance compared to traditional learning methods when processing large unstructured corpora.
This Special Issue aims at leveraging AI to improve healthcare delivery and management, and to promote fruitful collaborations between different disciplines, including applied mathematics, computer science, medical informatics, computational biology, clinical medicine, and healthcare research.
We invite submission of high-quality manuscripts reporting relevant research in the area of collecting, learning, mining, and understanding various bioinformatics data. Topics of interest include, but are not limited to:
- Knowledge acquisition, cleaning and assembly from structured and unstructured biomedical data silos;
- Knowledge analysis and discovery from large, temporal and uncertainty-ridden healthcare data;
- Medical data query processing and computing;
- Multimodal knowledge representation and fusion;
- Biomedical data management;
- Healthcare planning with big data evaluation and assessment;
- Data mining and machine learning algorithms for clinical solutions;
- Data-driven medical decision support system design;
- Electronic medical record data security and privacy.
Dr. Dagang Li
Dr. Ying Shen
Guest Editors
Manuscript Submission Information
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Keywords
- big data
- data mining
- machine learning
- healthcare
- health assessment
- disease treatment
- disease prevention
- infectious diseases
- chronic diseases
- epidemiology
- mental health
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