A Deep Learning Model that Diagnosis Skin Diseases and Recommends Medication

Rayan Shaik, Sai Krishna Bodhapati, Abhiram Uddandam, Lokesh Krupal, Joydeep Sengupta
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引用次数: 2

Abstract

Skin diseases are very common and the diagnosis is tricky and challenging. Latest research in the field of medicine along with the help of advanced technology has proved to be quite useful not only in diagnosis but also for treatment. Application of deep learning methods for diagnosis of skin diseases has given remarkable results. Computer aided results are quick and provide a quick overview of the disease.This paper aims to diagnose the skin disease from the infected skin image captured and provide details of the disease and recommend medication. To achieve this we have used stateof-the-art convolutional neural network(CNN) architecture MobileNetV2 for model building and training.This is particularly helpful for both doctors and individuals to analyze the disease. For doctors, they can validate their opinion with this prediction and individuals can have an idea of the disease at the beginning itself and can be helpful to prevent the disease further since prevention is always better than cure.
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诊断皮肤疾病并推荐药物的深度学习模型
皮肤病很常见,诊断很棘手,也很有挑战性。在医学领域的最新研究以及先进技术的帮助下,不仅在诊断方面而且在治疗方面都证明是非常有用的。深度学习方法在皮肤病诊断中的应用已经取得了显著的效果。计算机辅助的结果是快速的,并提供疾病的快速概述。本文的目的是从被感染的皮肤图像中诊断皮肤疾病,并提供疾病的细节和推荐药物。为了实现这一目标,我们使用了最先进的卷积神经网络(CNN)架构MobileNetV2进行模型构建和训练。这对医生和个人分析疾病都特别有帮助。对于医生来说,他们可以通过这种预测来验证他们的意见,个人可以在一开始就对疾病有一个了解,并且可以帮助进一步预防疾病,因为预防总是比治疗好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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