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Breast cancer detection based on thermographic images using machine learning and deep learning algorithms

Abstract

According to the latest data, breast carcinoma is the most prevalent kind of cancer in the world, and it is responsible for the deaths of almost 900 thousand people each year. If the disease is detected at the early stage and diagnosed properly, it can improve the chance of positive outcomes, thus reducing the fatality rate. An early diagnosis in fact can help in preventing it to spread and saves the premature victims from obtaining it. When trying to distinguish among benign and malignant tumors, as well as when trying to draw conclusions about mild and advanced breast cancer, researchers who study cancer encounter a number of challenges. The identification of all tumors is accomplished through the application of machine learning, which makes use of algorithms that are able to locate and recognize patterns. All of them, however, revolve around the concept of

Infrared Thermography in MedicineSmart Systems and Machine LearningAI in cancer detectionBreast cancerMachine learningArtificial intelligenceStage (stratigraphy)AlgorithmCancerIdentification (biology)DiseaseCase fatality rateComputer science
Citations
205
FWCI
28.23
field-weighted impact
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11
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References
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International Journal of Statistics and Applied Mathematics · 2020 · 8 citations
International Journal of Statistics and Applied Mathematics
International Journal of Statistics and Applied Mathematics · 2018 · 81 citations
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