Hybrid machine learning model for the prediction of anaemia
2025-11-07
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Call for Papers
International Scientific Technical and Economic Research
Dear Authors.
We cordially invite you to submit your manuscripts to the journal International Scientific
Technical and Economic Research. The journal is an international academic publication with the international issue number: ISSN 2959-1309. It is dedicated to the publication of high quality research in the fields of science, technology and economics.
We welcome original research papers in all fields, including but not limited to the
following topics:
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computer science, information technology, biotechnology, etc;
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4. interdisciplinary: interdisciplinary research in multiple fields, such as the relationship
between science and technology innovation and economic development, the impact of
technology applications on society and the environment, etc.
Please follow the following requirements for the call for papers:
1. Originality: Your submitted paper must be original, with a repetition rate of less than
20%, and not published or submitted in other journals or conferences.
2. Academic quality: We value academic rigor and quality, so please ensure that your
research methods, data analysis, and paper structure meet academic standards.
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guidelines. We accept submissions in English language only.
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ensure that all authors have substantial contributions and are clearly listed in the paper.
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7. The journal charges a small page fee according to the quality of the paper; it is
recommended to indicate the fund project to the teacher; if there is a fund project, the page fee will be significantly reduced and other publication and mailing costs will be charged, and the publication cycle will take about 3 months.
We are committed to completing the review process in a short time and providing high
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If you have any questions or require further information, please feel free to contact our
editorial team. We look forward to receiving your valuable submissions!
Good luck!
Editorial Board of International Scientific Technical and Economic Research
Announcements
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Advancing groundwater vulnerability assessment to nitrate contamination: a comprehensive evaluation of index-based, statistical and machine learning approaches with sensitivity analysis
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Prediction of geothermal heat flow for sustainable energy applications with sparse geological data using machine learning
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Current Issue
Volume. 3, No. 4 (December 2025)
Published:
2025-10-04
