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An Efficient Automated Technique for Classification of Breast Cancer Using Deep Ensemble Model

Computer Systems Science & Engineering 2023年第7期46卷 897-911页

作者： Muhammad Zia Ur Rehman Jawad Ahmad Emad Sami Jaha abdullah marish ali Mohammed A.Alzain Faisal Saeed Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City University15 Bartholomew RowBirminghamB55JUUK

Breast cancer is one of the leading cancers among *** has the second-highest mortality rate in women after lung *** detection,especially in the early stages,can help increase survival ***,manual diagnosis of breast cancer is a tedious and time-consuming process,and the accuracy of detection is reliant on the quality of the images and the radiologist’s ***,computer-aided medical diagnosis has recently shown promising results,leading to the need to develop an efficient system that can aid radiologists in diagnosing breast cancer in its early *** research presented in this paper is focused on the multi-class classification of breast *** deep transfer learning approach has been utilized to train the deep learning models,and a pre-processing technique has been used to improve the quality of the ultrasound *** proposed technique utilizes two deep learning models,Mobile-NetV2 and DenseNet201,for the composition of the deep ensemble *** learning models are fine-tuned along with hyperparameter tuning to achieve better ***,entropy-based feature selection is *** cancer identification using the proposed classification approach was found to attain an accuracy of 97.04%,while the sensitivity and F1 score were 96.87%and 96.76%,*** performance of the proposed model is very effective and outperforms other state-of-the-art techniques presented in the literature.

关键词： Breast cancer image enhancement ensemble model transfer learning feature selection

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Integrating Blockchain Technology into Healthcare Through an Intelligent Computing Technique

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Computers, Materials & Continua 2022年第2期70卷 2835-2860页

作者： Asif Irshad Khan abdullah Saad Al-Malaise ALGhamdi Fawaz Jaber Alsolami Yoosef B.Abushark Abdulmohsen Almalawi abdullah marish ali Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003Uttar PradeshIndia

The blockchain technology plays a significant role in the present era of information *** the last few years,this technology has been used effectively in several *** has already made significant differences in human life,as well as is intended to have noticeable impact in many other domains in the forthcoming *** rapid growth in blockchain technology has created numerous new possibilities for use,especially for healthcare *** digital healthcare services require highly effective security methodologies that can integrate data security with the availablemanagement *** test and understand this goal of security management in Saudi Arabian perspective,the authors performed a numerical analysis and simulation through a multi criteria decision making approach in this *** authors adopted the fuzzy Analytical Hierarchy Process(AHP)for evaluating the effectiveness and then applied the fuzzy Technique forOrder of Preference by Similarity to Ideal Solution(TOPSIS)technique to simulate the validation of *** eliciting highly corroborative and conclusive results,the study referred to a real time project of diabetes patients’management application of Kingdom of Saudi Arabia(KSA).The results discussed in this paper are scientifically proven and validated through various analysis *** the present study can be a credible basis for other similar endeavours being undertaken in the domain of blockchain research.

关键词： Blockchain technology data management fuzzy logic AHP TOPSIS

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