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A groundbreaking study has introduced a machine learning system capable of predicting tongue diseases with 96.6% accuracy. This system analyzes tongue color features under various lighting conditions, utilizing six different machine learning algorithms. The research aims to enhance the reliability of tongue diagnostics, traditionally reliant on subjective assessments.
The study highlights the effectiveness of the XGBoost algorithm, which outperformed others in accuracy and precision. By analyzing over 5,000 tongue images, the system can identify health conditions such as diabetes and COVID-19 based on tongue color. This innovative approach signifies a promising future for AI applications in healthcare diagnostics.
• AI predicts tongue diseases with 96.6% accuracy using machine learning.
• XGBoost algorithm shows superior performance in tongue color analysis.
The study employs machine learning to analyze tongue images for disease prediction.
XGBoost was identified as the most accurate algorithm in the tongue disease prediction study.
The imaging system offers real-time analysis of tongue color to predict health conditions.
Amazon's advancements in AI technologies contribute to various applications, including healthcare diagnostics.
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