2019
DOI: 10.1016/j.annpat.2019.01.004
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Intelligence artificielle : quel avenir en anatomie pathologique ?

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Cited by 21 publications
(9 citation statements)
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“…Early determination of this cancer increases survival chances, but women residing in medically underserved areas do not have access to specialist doctors. Machine learning and cloud computing services have drawn the attention of various researchers for developing disease prediction systems, such as [70][71][72][73][74][75][76][77][78], as a feasible option in remote diagnostics, where cloud computing provided Platform-as-a-Service (PaaS) to obtain resources on demand.…”
Section: Performance Comparison Of Elm On the Cloud Environment And Standalone Environmentmentioning
confidence: 99%
“…Early determination of this cancer increases survival chances, but women residing in medically underserved areas do not have access to specialist doctors. Machine learning and cloud computing services have drawn the attention of various researchers for developing disease prediction systems, such as [70][71][72][73][74][75][76][77][78], as a feasible option in remote diagnostics, where cloud computing provided Platform-as-a-Service (PaaS) to obtain resources on demand.…”
Section: Performance Comparison Of Elm On the Cloud Environment And Standalone Environmentmentioning
confidence: 99%
“…The advantage of our method is to adapt the extracted features to the type of application being studied, which may be outside the scope of the images learned by the VGGNet network. Thus, our approach can be applied to biomedical images such as histopathological images [27,66] or vibration signals from a mechatronic system for industrial monitoring [20].…”
Section: Feature Reconstruction Lossmentioning
confidence: 99%
“…The CAD methods of BC aim to automatically classify breast findings as benign or malignant, using intelligent approaches. With the advent of whole slide digital scanners, complete slides can now be scanned to create and produce high-resolution digital files [ 4 , 5 ]. This opened the door to researchers and practitioners to carry out a quantitative analysis of histopathological images through developing reliable CAD tools that facilitate the detection and diagnosis of different diseases [ 4 , 5 ].…”
Section: Introductionmentioning
confidence: 99%