U.S. Food and Drug Administration

This regulatory science tool presents an open-access dataset tool for the assessment of wearable technology deriving gait parameters.

This regulatory science tool presents Python-based software for evaluating computer models that predict the number of COVID-19 deaths or hospitalizations expected in a specific locality.

This regulatory science tool presents a method (web-based decision tree) that may help developers select appropriate metric and endpoint for Artificial Intelligence (AI) / Machine learning (ML) classification algorithms in medical imaging.

This regulatory science tool presents a method to measure the radially variant contrast on virtual reality head-mounted displays (VR HMDs) using circular concentric ring patterns, which can be implemented to characterize image quality, including Michelson contrast and effective resolution, on VR HMDs equipped with optical lenses.

This regulatory science tool is a method for measuring the line spread function (LSF) and calculating the modulation transfer function (MTF) for head mounted displays (HMDs).

This regulatory science tool is a lab method that computes bone microstructure metrics to characterize bone morphology and skeletal geometry.

This regulatory science tool is a model for establishing analyte recovery in chemical characterization studies following liquid-liquid extraction.

This regulatory science tool is a lab method in the form of a physical mock circulation loop (MCL) used for simulating peripheral radial pressure waveforms.

This regulatory science tool is a lab method tool used for simulating target clinical use patient conditions on the bench using a mock circulatory loop in conjunction with the ISO 14708-5 standard specifications for circulatory support devices.

This regulatory science tool comprises a computer model of a human action potential, which includes the effects of heart failure (HF) and the anti-arrhythmic drugs amiodarone (AM) and d-sotalol (DS).