Fig. 1: Conceptual overview illustrating the contrast between traditional medical diagnosis and machine learning-based interpretation of knee acoustic emissions. | npj Biomedical Innovations

Fig. 1: Conceptual overview illustrating the contrast between traditional medical diagnosis and machine learning-based interpretation of knee acoustic emissions.

From: A robust and interpretable deep transfer learning framework on knee acoustic emissions for osteoarthritis classification

Fig. 1

The left panels represent the conventional clinical workflow, where diagnostic reasoning is based on symptoms, imaging, and anatomical cues. The right panels show the proposed AI-based approach, where knee sounds are analyzed by a machine learning model, and the decision process is made transparent via explainable AI techniques. The illustrative analogy (e.g., highlighting a dog in an image) emphasizes how the model focuses on acoustically meaningful regions.

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