Forthcoming articles

 


International Journal of Functional Informatics and Personalised Medicine

 

These articles have been peer-reviewed and accepted for publication in IJFIPM, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

 

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

 

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

 

Articles marked with this Open Access icon are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

 

Register for our alerting service, which notifies you by email when new issues of IJFIPM are published online.

 

We also offer RSS feeds which provide timely updates of tables of contents, newly published articles and calls for papers.

 

International Journal of Functional Informatics and Personalised Medicine (2 papers in press)

 

Regular Issues

 

  • An Overview of Real-world Clinical Data Mining on TCM   Order a copy of this article
    by Xiaoping Zhang 
    Abstract: This paper provides a survey of commonly used data mining methods that have been applied to real-world TCM clinical data in recent years, and sets forth the requirements of data mining on real-world TCM clinical data, in order to provide reference for better analyzing the syndrome differentiation and treatment principle hidden in the massive TCM clinical data in the future.
    Keywords: Real-world; data mining; Traditional Chinese medicine (TCM); clinical diagnosis and treatment.

  • Predicting and Analyzing Breast Cancer tumors by adopting Hybrid Neuro Fuzzy approach   Order a copy of this article
    by Sanjiban Sekhar Roy, Saptarshi Chakraboty, P.V. Krishna, Ajith Abraham 
    Abstract: It is often observed and criticized that health experts demonstrate variability in treatment while making crucial decisions regarding the diagnosis of a patient. These variations of decision making not only depends upon the condition of the patient; but also the doctors experience in that particular field plays a huge part in such crucial decision making. To solve these types of problem, researchers and medical experts have suggested setting a standard set of parameters to analyze the different conditions. Automated (computerized) models were also proposed as these models dont exhibit this variability while making crucial decisions. The benefit of computerized model is its consistency and accuracy in decision making. In this paper, we have proposed a hybrid model to simulate a breast cancer treatment scenario based on the medical history of the patients stored in the hospital database. Our proposed approach can detect whether the tumor is benign or malignant based on the assessment of nine different biological attributes. We have tested the performance of our proposed model on the Wisconsin Breast Cancer Database and compared the result obtained from our proposed approach with the other existing machine learning techniques. Through different experiments, we have established the effectiveness of our proposed algorithm.
    Keywords: Neuro-Fuzzy; Breast Cancer; Hybrid Method; ANFIS.