Table 4 Reported performance for prostate cancer grading and scoring using deep learning models
Reference | Classes | Results | #Patients | Annotations | Multicenter |
|---|---|---|---|---|---|
Arvaniti [14] | GS6,GS7,GS8,GS9,GS10 | \(\kappa = 0.75\) | 641 | Strong | No |
Nagpal [10] | GS6,GS7,GS8,GS9,GS10 | ACC\(= 0.70\) | 342 | Strong | Yes |
Burlutskiy [11] | With/out basal cells | \(F_{1} = 0.80\) | 229 | Strong | No |
Ström [12] | ISUP: 1,2,3,4,5 | \(\kappa = 0.67\) | 976 | Strong | Yes |
Otálora [8] | GS6, GS7, GS8, GS9, GS10 | \(\kappa = 0.44\) | 341 | Weak | Yes |
This work | ISUP: 1,2,3,4,5 | \(\kappa = 0.52\) | 341 WSI + 641 TMA | Weak and strong | Yes |
Arvaniti [15] | ISUP: 1,2,3,4,5 | \(\tau = 0.54\) | 447 WSI + 641 TMA | Weak and strong | Yes |
Bulten [7] | ISUP: 1,2,3,4,5 | \(\kappa = 0.72\) | 1243 | Weak and strong | Yes |
Campanella [9] | Benign versus cancer | AUCs of 0.98 | 7159 | Weak | Yes |