Important Date
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Submission
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Notification
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Registration Deadline
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Conference
Date
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Jan. 10, 2025
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Feb. 10, 2025
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Feb. 25, 2025
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May 16-18, 2025
Welcome to ICMHI 2025 | Flyer
We are pleased to announce that 2025 9th International Conference on Medical and Health Informatics (ICMHI 2025) will be held in Kyoto, Japan during May 16-18, 2025. The ICMHI 2025 aims to bring together outstanding scholars, researchers, and students to exchange and share their experiences and research results about all aspects of Medical and Health Sciences. We also provide the keynote address and several plenary invited speeches for discuss the most recent innovations, trends, and concerns, practical challenges encountered and the various solutions in the fields of medical and health informatics. We cordially welcome all experts of industry, academia and government from all over the world to contribute to and help shape this conference through submissions of their research abstracts, papers and posters. Eventually, the ICMHI 2025 facilitates interdisciplinary collaboration and exchange among technologists internationally.
Publication
Accepted papers of ICMHI 2025 will be published in international conference proceedings.
Publication Ethics - Penalty against
Plagiarism
We firmly believe that ethical conduct is the most essential virtual
of any academic. Hence any act of plagiarism is a totally
unacceptable academic misconduct and cannot be tolerated.
Call For Papers
The ICMHI 2025 solicits contributions of abstracts, full papers and posters that address themes and topics of the conference. The topics of interest include, but not limited to the following:
·Biomedical Data mining
·Biomedical Engineering
·Cloud Computing &Applications
·Big Data for Healthcare Practices
·Collaboration Technologies for Healthcare
·Computational Intelligence Methodologies
·Medical Robotics & Information Security
·Survival Analysis &Health Hazard
·Personalized Treatment
·E-commerce in Health Informatics
·Epidemiological Modeling
·Health Informatics Education
·Medical Image Processing
·Medical Insurance Fraud Detection
·Statistics & Quality of Medical Data