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Ekins Kuuzie
commited on
Updating the content of the article and description
Browse files
app.py
CHANGED
@@ -38,11 +38,22 @@ platform = gr.Interface( fn = predict_image,
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title ="TB CADx",
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inputs = "image",
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outputs = "label",
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description="""
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clinicians
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the
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platform.launch(inline=True, share=True)
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title ="TB CADx",
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inputs = "image",
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outputs = "label",
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description="""
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Introducing a revolutionary computer-aided detection tool designed to enhance the efficiency of clinicians in the classification of chest X-ray images.
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This innovative system facilitates the swift classification of images into three key categories: normal, indicating no abnormalities;
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unhealthy but not indicative of Tuberculosis (TB); and those with a high likelihood of TB presence.
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By streamlining the classification process, this tool aims to expedite diagnostic assessments and aid clinicians in making informed decisions regarding patient care.
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""",
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article = """
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It is crucial to emphasize that while this tool serves as a valuable research aid,
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it is not intended to replace clinical guidelines,
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nor should it substitute for the wealth of clinical knowledge
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and experience possessed by healthcare professionals.
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The algorithm is meant to complement and support the diagnostic process,
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providing an additional layer of analysis for consideration in conjunction with the clinician's expertise.
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Users are encouraged to interpret the algorithm's output in conjunction with their clinical judgment,
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and the tool should be viewed as a supplementary resource rather than a standalone diagnostic solution.
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""" )
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platform.launch(inline=True, share=True)
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