Transferred Semantic Scores for Scalable Retrieval of Histopathological Breast Cancer Images

Nejad, Elaheh Mahraban; Affendey, Lilly Suriani; Latip, Rohaya; Ishak, Iskandar; Banaeeyan, Rasoul

doi:10.1007/s13735-018-0157-z

Cited by 15 publications

(2 citation statements)

References 23 publications

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“…The review methodology is consistent with the work conducted by [45]. Therefore, prior studies that showed systematic review or systematic mapping approaches are applied with minor differences [51][52][53][54][55][56][57]; however, there are overlapping phases or processes, such as the identification of studies, selection, quality assessment, data extraction, and data synthesis [51,52,[58][59][60][61][62][63][64]. For example, reference [54] splits the selection phase into the development of inclusion or exclusion criteria and selected studies for inclusion and exclusion criteria.…”

Section: Methodsmentioning

confidence: 99%

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

et al. 2022

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The end goal of technological advancement used in crisis response and recovery is to prevent, reduce or mitigate the impact of a crisis, thereby enhancing sustainable recovery. Advanced technological approaches such as social media, machine learning (ML), social network analysis (SNA), and big data are vital to a sustainable crisis management decisions and communication. This study selects 28 articles via a systematic process that focuses on ML, SNA, and related technological tools to understand how these tools are shaping crisis management and decision making. The analysis shows the significance of these tools in advancing sustainable crisis management to support decision making, information management, communication, collaboration and cooperation, location-based services, community resilience, situational awareness, and social position. Moreover, the findings noted that managing diverse outreach information and communication is increasingly essential. In addition, the study indicates why big data and language, cross-platform support, and dataset lacking are emerging concerns for sustainable crisis management. Finally, the study contributes to how advanced technological solutions effectively affect crisis response, communication, decision making, and overall crisis management.

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Section: Methodsmentioning

confidence: 99%

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

et al. 2022

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“…This methodology implements three steps of a process lower-level feature extraction, med-level feature extraction, and med-level feature vectors, which are used in the online-based retrieval of images. Here, the query image is also applied in the concept of mid-level descriptors [24].…”

Section: Literature Surveymentioning

confidence: 99%

Scale Invariant Feature Transform with Crow Optimization for Breast Cancer Detection

Selvi¹,

Thilagamani²

2023

Intelligent Automation &Amp; Soft Computing

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Mammography is considered a significant image for accurate breast cancer detection. Content-based image retrieval (CBIR) contributes to classifying the query mammography image and retrieves similar mammographic images from the database. This CBIR system helps a physician to give better treatment. Local features must be described with the input images to retrieve similar images. Existing methods are inefficient and inaccurate by failing in local features analysis. Hence, efficient digital mammography image retrieval needs to be implemented. This paper proposed reliable recovery of the mammographic image from the database, which requires the removal of noise using Kalman filter and scale-invariant feature transform (SIFT) for feature extraction with Crow Search Optimizationbased the deep belief network (CSO-DBN). This proposed technique decreases the complexity, cost, energy, and time consumption. Training the proposed model using a deep belief network and validation is performed. Finally, the testing process gives better performance compared to existing techniques. The accuracy rate of the proposed work CSO-DBN is 0.9344, whereas the support vector machine (SVM) (0.5434), naïve Bayes (NB) (0.7014), Butterfly Optimization Algorithm (BOA) (0.8156), and Cat Swarm Optimization (CSO) (0.8852).

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Domain and Histopathology Adaptations–Based Classification for Malignancy Grading System

Mudeng,

Farid,

Ayana

et al. 2023

The American Journal of Pathology

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Transferred Semantic Scores for Scalable Retrieval of Histopathological Breast Cancer Images

Cited by 15 publications

References 23 publications

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review

Scale Invariant Feature Transform with Crow Optimization for Breast Cancer Detection

Domain and Histopathology Adaptations–Based Classification for Malignancy Grading System

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