Identification and Grouping of Skin Sickness by Means of Deep Learning

Udupa, Pradeep; Naidu, Aishwarya V. K.; Shettigar, Suraj Kumar; Maurya, Jayender Bahadur

doi:10.1007/s42979-022-01637-5

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Machine Learning1

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2023

2024

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Cited by 2 publications

(1 citation statement)

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“…1.3. Literature review Some concrete and recent applications of CNNs in the medical field are, for example, diagnosis of Alzheimer's disease and prediction of the progression of intellectual decay [13], lung cancer detection and classification [14,15], detection of injuries on chest X-ray [16], identification and grouping of skin diseases [17], even the detection of certain diseases in crops [18]. There are also recent studies and CNN designs in the specific field to be addressed, Id.…”

Section: Machine Learningmentioning

confidence: 99%

Helping Breast Cancer Diagnosis on Mammographies using Convolutional Neural Networks

García-Mojón,

Martín-Rodríguez,

Fernández-Barciela

2024

Preprint

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In this paper a study about breast cancer detection is presented. Mammography images in DICOM format are processed using Convolutional Neural Networks (CNN’s) to get a pre-diagnosis. Of course, this preliminary result needs to be checked by a trained radiologist. CNN’s are trained and checked using a big database that is publicly available. Standard measurements for success are computed (accuracy, precision, recall) obtaining outstanding results better than other examples from the literature.

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