L
Leila Shahmoradi
Researcher at Tehran University of Medical Sciences
Publications - 111
Citations - 1912
Leila Shahmoradi is an academic researcher from Tehran University of Medical Sciences. The author has contributed to research in topics: Medicine & Health care. The author has an hindex of 17, co-authored 92 publications receiving 1214 citations. Previous affiliations of Leila Shahmoradi include University of Tehran & Iran University of Medical Sciences.
Papers
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A knowledge-based system for breast cancer classification using fuzzy logic method
TL;DR: Experimental results on Wisconsin Diagnostic Breast Cancer and Mammographic mass datasets show that proposed methods remarkably improves the prediction accuracy of breast cancer.
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The application of internet of things in healthcare: a systematic literature review and classification
Hossein Ahmadi,Hossein Ahmadi,Goli Arji,Leila Shahmoradi,Reza Safdari,Mehrbakhsh Nilashi,Mehrbakhsh Nilashi,Mojtaba Alizadeh +7 more
TL;DR: It was revealed that home healthcare service was one of the main application areas of IoT in healthcare, and the main challenges of Internet of Things in healthcare were security and privacy issues.
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An analytical method for diseases prediction using machine learning techniques
TL;DR: The results showed that the combination of fuzzy rule-based, CART with noise removal and clustering techniques can be effective in diseases prediction from real-world medical datasets.
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Hospital Information System adoption
TL;DR: Results indicated that the developed integrated framework provides an effective prediction of the HIS adoption by Malaysian public hospitals.
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Diseases diagnosis using fuzzy logic methods: A systematic and meta-analysis review.
Hossein Ahmadi,Marsa Gholamzadeh,Leila Shahmoradi,Mehrbakhsh Nilashi,Mehrbakhsh Nilashi,Pooria Rashvand +5 more
TL;DR: This study approved the effectiveness of applying different fuzzy methods in diseases diagnosis process, presenting new insights for researchers about what kind of diseases which have been more focused will help to determine the diagnostic aspects of medical disciplines that are being neglected.