{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np\nimport pandas as pd \nimport os","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### DCM extention \n\nFiles that contain the .dcm file extension are most commonly associated with image files that have been saved in the DICOM image format.\n\nDICOM stands for Digital Imaging and Communications in Medicine. This file format was created as a way to distribute and view medical images using a standardized file format.\n\nThe DCM file format was developed by the National Electrical Manufacturers Association. In addition to medical images, DCM files may also contain patient information.\n\nThe DiskCatalogMaker software application has also been known to use the .dcm file suffix. This program uses the .dcm file extension when saving catalog files that have been created with the software."},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"df_sample=pd.read_csv(\"/kaggle/input/rsna-intracranial-hemorrhage-detection/stage_1_sample_submission.csv\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train=pd.read_csv(\"/kaggle/input/rsna-intracranial-hemorrhage-detection/stage_1_train.csv\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_sample.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_train['Label'].unique()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import seaborn as sns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sns.countplot(df_train.Label)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Ack: https://www.kaggle.com/mobassir/keras-efficientnetb4-for-intracranial-hemorrhage"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":1}