Determinants of cone- and rod-function in geographic atrophy: AI-based structure-function correlation by Pfau, M, von der Emde, L, Dysli, C, Möller, PT, Thiele, S, Lindner, M, Schmid, M, Rubin, DL, Fleckenstein, M, Holz, FG, Schmitz-Valckenberg, S

“…</p> <p><strong>Results</strong> Retinal sensitivity was predicted with a MAE of 4.64 dB for mesopic, 4.89 dB for DA cyan and 4.40 dB for DA red testing in absence of patient-specific data. …”

Artificial intelligence for morphology-based function prediction in neovascular age-related macular degeneration by von der Emde, L, Pfau, M, Dysli, C, Thiele, S, Möller, PT, Lindner, M, Schmid, M, Fleckenstein, M, Holz, FG, Schmitz-Valckenberg, S

“…With patient-wise leave-one-out cross-validation, we have been able to achieve prediction accuracies of (mean absolute error, MAE [95% CI]) 3.94 dB [3.38, 4.5] for mesopic, 4.93 dB [4.59, 5.27] for DA cyan and 4.02 dB [3.63, 4.42] for DA red testing. …”

Light sensitivity within areas of geographic atrophy secondary to age-related macular degeneration by Pfau, M, von der Emde, L, Dysli, C, Thiele, S, Möller, PT, Lindner, M, Nadal, J, Schmid, M, Schmitz-Valckenberg, S, Holz, FG, Fleckenstein, M

“…</p> <p><strong>Methods:</strong> Mesopic and dark-adapted (DA) cyan and red light sensitivity (Goldmann III) were investigated using fundus-controlled perimetry (microperimetry). …”