ArticleComputational and mathematical methods in medicine2020
A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules.
Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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- Standalone deep learning versus experts for diagnosis lung cancer on chest computed tomography: a systematic review.European radiology · 2024Pooled it
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Abstract
backgroundThe differential diagnosis of subcentimetre lung nodules with a diameter of less than 1 cm has always been one of the problems of imaging doctors and thoracic surgeons. We plan to create a deep learning model for the diagnosis of pulmonary nodules in a simple method.
methodsImage data and pathological diagnosis of patients come from the First Affiliated Hospital of Zhejiang University School of Medicine from October 1, 2016, to October 1, 2019. After data preprocessing and data augmentation, the training set is used to train the model. The test set is used to evaluate the trained model. At the same time, the clinician will also diagnose the test set.
resultsA total of 2,295 images of 496 lung nodules and their corresponding pathological diagnosis were selected as a training set and test set. After data augmentation, the number of training set images reached 12,510 images, including 6,648 malignant nodular images and 5,862 benign nodular images. The area under the
conclusionWith the help of an automatic machine learning system, clinicians can create a deep learning pulmonary nodule pathology classification model without the help of deep learning experts. The diagnostic efficiency of this model is not inferior to that of the clinician.
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