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pydicom

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Developed and evaluated two models, to detect pneumonia cases from medical images. Our custom resnet18 was evaluated at an 81% accuracy, 66% precision, and 78% recall. Valuable for timely detection of pneumonia patients, improving outcomes, and reducing mortality. CAM visualizations provide provide insights into model decision-making

  • Updated Jul 18, 2023
  • Jupyter Notebook

This project focuses on building a model that predicts the age and contrasts amongst the medical images of skin diseases of 9 types. The dataset was taken from kaggle and was devided into train and validation images..

  • Updated Jun 17, 2024
  • Jupyter Notebook

Поиск файлов исследований КТ по заданным параметрам (в примере- исследования легких), их копирование и анонимизация, а так же отправка на сервер обработки и получение результатов с уведомлением по электронной почте.

  • Updated Jan 20, 2021
  • Python

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