Stanford Bone Bayes is a Bayesian network that models clinical and radiographic inputs to compute diagnosis, differential diagnosis, and probabilities.
Read the Stanford Bone Bayes publication here.
Here is a tutorial on how to select features.
Christopher Beaulieu MD PhD ( link )
Bao Do MD ( link )
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Age ( years ) :
Gender :
male
female
# of lesions :
solitary
multiple
Bone location :
Longitudinal location :
Proximal or distal :
Transverse location :
Central vs eccentric :
central
eccentric
not applicable
Density :
Matrix / texture :
Transition zone / border :
Cortex :
Periosteum :
Lesion to shaft ratio :
0-25%
25-50%
50-75%
75-100%
> 100%
not applicable
Physis :
closed
open
Expansion :
non-expansile
expansile
Associated soft tissue mass :
yes
no
Associated pathologic fracture :
yes
no
Knowledge source :
Stanford Jones, Dahlin, Campanacci, Pai & Yap literature review (July 2020)
What is your top (1-3) differential diagnosis ? ( Please help us train the A.I. )
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