CFP: SI with IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

Dear authors/professors/scientists, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) is a well reputable journal in the fields of computational biology, healthcare engineering, bio-medical research and bioinformatics. Based on evaluation on your existing publications in the related fields, we would like to invite you to contribute one article/review to the special issue: “Machine Learning for AI-Enhanced Healthcare and Medical Services: New Development and Promising Solution” with IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB, IF=2.428, deadline: 30 Dec 2018). The topics of interest include, but not limited to the following topics: - AI enhanced clinical decision making; - Biomechanics, modeling and computing; - AI based computer vision topics on medical images; - Big data research and project experience in bio-medical and healthcare services; - Knowledge-based or agent-based models for biological systems; - Distributed systems in medical and healthcare services; - Intelligent devices and instruments for medical and healthcare services; - Machine learning in medicine, human biology, and healthcare; - Intelligent and process-aware information systems in human biology, healthcare and medicine; - AI and data science for human biology, medical and healthcare services; - AI in medical and healthcare education. To submit your works, simply log into the TCBB journal online submission system (https://mc.manuscriptcentral.com/tcbb-cs) followed by selecting the option: ‘SI-MLHealth-2018’ by 30 Dec 2018. For detailed information, please refer to the CFP flyer attached to this email. Please kindly notice that all submissions to the SI will go through a formal review process with at least three professional reviewers in the related field. We will try our best to return the review comments to you within a month after your submission. Whether your paper will be accepted by the journal will strictly depend on the reviewers’ recommendation. Best regards, Ke Yan (Ph.D.) Leading/Corresponding guest editor, Associate Professor, China Jiliang University
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