Data Analysis and Machine Learning in Healthcare
A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Health Informatics and Big Data".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 501
Special Issue Editor
Interests: data science; machine learning; digital health
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Data analysis and machine learning are rapidly transforming the healthcare industry by enabling the extraction of valuable insights from vast and complex datasets. With the increasing availability of data from electronic health records (EHRs), medical imaging, genomics, and wearable devices, these technologies are becoming indispensable tools in improving patient care, optimizing healthcare operations, and reducing costs. The integration of data analysis and machine learning into healthcare practices has the potential to revolutionize diagnostics, personalize treatments, and enhance decision-making processes, making this a critical area of research and development.
We are pleased to invite you to contribute to a Special Issue focused on "Data Analysis and Machine Learning in Healthcare", which aligns with the journal's commitment to advancing knowledge and practice in healthcare and medical informatics. This Special Issue aims to explore the latest advancements and applications of data analysis and machine learning in healthcare, emphasizing their role in improving patient outcomes, enhancing healthcare delivery, and supporting evidence-based decision-making. By bringing together cutting-edge research and innovative methodologies, this Special Issue seeks to provide a comprehensive overview of how these technologies are reshaping the future of healthcare.
In this Special Issue, we welcome original research articles and reviews that cover a broad range of topics related to data analysis and machine learning in healthcare. Suggested themes for submissions include, but are not limited to, the following:
- Development and application of machine learning algorithms in healthcare;
- Predictive analytics for disease diagnosis and treatment;
- Natural language processing for healthcare data interpretation;
- Image and signal processing using machine learning techniques;
- Integration of genomic and multi-omics data in personalized medicine;
- Optimization of healthcare operations and resource allocation through data-driven approaches.
We look forward to receiving your contributions and advancing the understanding and application of data analysis and machine learning in the realm of healthcare.
Dr. Farshid Hajati
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. Healthcare 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 2700 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.
Keywords
- machine learning in healthcare
- predictive analytics
- personalized medicine
- healthcare data interpretation
- medical imaging analysis
- genomic data integration
- natural language processing (NLP)
- healthcare operation optimization
- signal processing in healthcare
- evidence-based decision-making
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