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BRAIN TUMOR CLASSIFICATION

A machine learning package that diagnoses brain tumors from MRI (Magnetic Resonance Imaging) scans. It detects if there is a tumor and then classify it in terms of grade, type, and specific location. This program uses a neural network algorithm to detect tumors/no tumors with a validation accuray of 92% and a validation recall of 98%.

Data set and its description

Data Description
Image the image object(jpg format)
Label class options of each image (glioma, meningioma, no tumor, and pituitary.)

Dependencies and packages

  1. numpy>=1.20.0,<1.21.0
  2. python = 3.10
  3. pandas = 2.2.2
  4. scikit-learn = 1.4.2
  5. pydantic = 2.7.0
  6. strictyaml = 1.7.3
  7. tensorflow = 2.16.1
  8. scikeras = 0.13.0
  9. tensorflow-datasets = 4.9.4
  10. pillow = 10.3.0
  11. pydantic-settings = 2.2.1
  12. fastapi = 0.110.3
  13. uvicorn = 0.29.0
  14. loguru = 0.7.2
  15. python-multipart = 0.0.9

Source code link: Github link

Python index package: Pypi link

Release files for braintumor-model-package 0.2.0

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Source distribution for braintumor-model-package 0.2.0
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Table of built distributions (wheels) for braintumor-model-package 0.2.0
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Total release size: 161.6 MB

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0.2.0 This release

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0.1.0

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