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Evaluating diagnostic accuracy of generalized pustular psoriasis with the Legit.Health device

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Evaluating diagnostic accuracy of generalized pustular psoriasis (GPP) with the Legit.Health device

This is the Python code used for the analysis presented in "Evaluating diagnostic accuracy of generalized pustular psoriasis with the Legit.Health device".

The goal of the study was to assess whether Legit.Health, a medical device powered by artificial intelligence (AI), could correctly identify GPP out of a large set of possible skin conditions. Results showed a marked improvement in the ability of healthcare practitioners to diagnose GPP correctly with the help of Legit.Health. This highlights the potential of this AI-powered medical device to support healthcare practitioners in identifying rare diseases such as GPP, particularly in general practice settings where they may not be equipped to diagnose rare diseases. Legit.Health’s technology can empower healthcare practitioners to make more accurate diagnoses, ultimately improving patient outcomes.

Requirements

The analysis was conducted using Python 3.12 and the following packages:

  • numpy
  • pandas
  • statsmodels

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Evaluating diagnostic accuracy of generalized pustular psoriasis with the Legit.Health device

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