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A groundbreaking AI model, ECgMPL, developed by an international team including Charles Darwin University, demonstrates a remarkable 99.26% accuracy in identifying endometrial cancer. This model significantly outperforms traditional diagnostic methods, which have an accuracy rate of only 78.91% to 80.93%. The AI's ability to analyze microscopic images allows for early detection of cancer, which is crucial for effective treatment.
The ECgMPL model is not limited to endometrial cancer; it can also be adapted for diagnosing other types of cancer, such as colorectal and oral cancer, with high accuracy rates. This innovative approach combines advanced deep learning techniques to enhance image quality and pinpoint problematic growths that may be missed by human eyes. The model is designed to assist medical professionals rather than replace them, providing a faster and more accessible diagnostic tool.
• AI model ECgMPL achieves 99.26% accuracy in cancer detection.
• Model can adapt to diagnose various types of cancer effectively.
Deep learning algorithms are utilized to enhance image quality and identify cancerous growths.
Histopathology images are analyzed by the AI to detect early stages of cancer.
Charles Darwin University is involved in developing the ECgMPL AI model for cancer diagnosis.
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