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Table 4 Experimental results of the NLP algorithm for each fracture type

From: Natural language processing of radiology reports for identification of skeletal site-specific fractures

Fractures Sensitivity Specificity PPV NPV F1-score
Ankle 0.974 1.000 1.000 0.974 0.987
Clavicle 1.000 1.000 1.000 1.000 1.000
Distal Forearm 1.000 1.000 1.000 1.000 1.000
Face 0.760 1.000 1.000 0.806 0.864
Feet and Toes 0.960 1.000 1.000 0.962 0.980
Hand and Fingers 0.918 1.000 1.000 0.924 0.957
Other Spine Fractures 0.875 1.000 1.000 0.889 0.933
Patella 1.000 1.000 1.000 1.000 1.000
Pelvis 0.952 1.000 1.000 0.955 0.976
Proximal Femur 1.000 1.000 1.000 1.000 1.000
Proximal Humerus 1.000 1.000 1.000 1.000 1.000
Ribs 0.933 1.000 1.000 0.938 0.966
Scapula 1.000 1.000 1.000 1.000 1.000
Shaft and Distal Femur 0.800 1.000 1.000 0.833 0.889
Shaft and Distal Humerus 0.857 1.000 1.000 0.875 0.923
Shaft and Proximal Radius/Ulna 0.952 1.000 1.000 0.955 0.976
Skull 1.000 1.000 1.000 1.000 1.000
Sternum 1.000 1.000 1.000 1.000 1.000
Tibia and Fibula 0.944 1.000 1.000 0.947 0.971
Vertebral Body 0.675 1.000 1.000 0.755 0.806
Micro-Average 0.930 1.000 1.000 0.941 0.961