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Analysis of an electronic methods for nasopharyngeal carcinoma: Prevalence, diagnosis, challenges and technologies.

, , , and . J. Comput. Sci., (2017)

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Analysis of an electronic methods for nasopharyngeal carcinoma: Prevalence, diagnosis, challenges and technologies., , , and . J. Comput. Sci., (2017)A real time computer aided object detection of nasopharyngeal carcinoma using genetic algorithm and artificial neural network based on Haar feature fear., , , , , and . Future Gener. Comput. Syst., (2018)Secure blockchain assisted Internet of Medical Things architecture for data fusion enabled cancer workflow., , , , , , , and . Internet Things, (December 2023)Electronic health records approaches and challenges: a comparison between Malaysia and four East Asian countries., , , , and . Int. J. Electron. Heal., 4 (1): 78-104 (2008)Neural network and multi-fractal dimension features for breast cancer classification from ultrasound images., , , , , and . Comput. Electr. Eng., (2018)Multi-Agent Systems in Fog-Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring., , , , , , and . Sensors, 21 (20): 6923 (2021)Trainable model for segmenting and identifying Nasopharyngeal carcinoma., , , , , and . Comput. Electr. Eng., (2018)An analysis of the healthcare informatics and systems in Southeast Asia: a current perspective from seven countries., , , , , , , , , and . Int. J. Electron. Heal., 4 (2): 184-207 (2008)Automatic segmentation and automatic seed point selection of nasopharyngeal carcinoma from microscopy images using region growing based approach., , , , and . J. Comput. Sci., (2017)Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson's disease., , , , , , , and . Cogn. Syst. Res., (2019)