医学
机器学习
人工智能
接收机工作特性
阑尾炎
急性阑尾炎
医学诊断
逻辑回归
人工神经网络
支持向量机
随机森林
诊断准确性
放射科
计算机科学
外科
作者
Shaan Bhandarkar,Ayaka Tsutsumi,Eric B. Schneider,Chin Siang Ong,Lucero G. Paredes,Alexandria Brackett,Vanita Ahuja
摘要
Appendicitis is an inflammatory condition that requires timely and effective intervention. Despite being one of the most common surgically treated diseases, the condition is difficult to diagnose because of atypical presentations. Ultrasound and computed tomography (CT) imaging improve the sensitivity and specificity of diagnoses, yet these tools bear the drawbacks of high operator dependency and radiation exposure, respectively. However, new artificial intelligence tools (such as machine learning) may be able to address these shortcomings.
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