Adaptive Sensory Technology, Inc.

The Ohio State University

The Schepens Eye Research Institute, Inc.

Michael Dorr

Luis A Lesmes

Zhong-Lin Lu

Peter Bex

Disclosed herein are methods and systems of evaluating test-retest precision using fractional rank precision or mean-average precision, comprising: a) collecting a test and a retest result of each subject, wherein the results are described in feature space(s) and collected from a vision test machine; b) selecting, a first test result of a first subject; c) calculating distances from the first test result to the retest result of each subject; d) assessing, a similarity between the first test result and the retest result of each subject by ranking the distances in a non-descending order; e) assessing a rank precision for the first subject based on a rank of a distance from the first test result to the retest result of the first subject; f) repeating b), c), d), and e) for each subject; and evaluating, the test-retest precision based on the rank precision for each of the plurality of subjects.

Methods and systems using fractional rank precision and mean average precision as test-retest reliability measures

Data is received characterizing a result of a first visual sensitivity test assessing capacity to detect spatial form across one or more different target sizes, and different contrasts. Using the received data, one or more first parameters defining a first estimated visual sensitivity for a first range of contrasts and a second range of spatial frequencies is determined. One or more second parameters defining a second estimated visual sensitivity for a third range of contrasts and a fourth range of spatial frequencies is determined using the one or more first parameters and a statistical inference by at least presenting a first visual stimulus, receiving a response, and determining a second visual stimulus based at least on the response and at least a rule. The one or more second parameters is provided. Related apparatus, systems, techniques and articles are also described.

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Michael Dorr