Methods and systems for embryo classification using morpho-kinetic signatures

A method of classifying morpho-kinetic signatures in embryos, the method comprising:

• receiving, using control circuitry, a first morpho-kinetic signature of a first embryo, wherein the first morpho-kinetic signature is a representation of morpho-kinetic events in the first embryo as a function of time;
• labeling, using the control circuitry, the first morpho-kinetic signature with a known classification;
• training, using the control circuitry, an artificial neural network to detect the known classification based on the first morpho-kinetic signature;
• receiving, using the control circuitry, a second morpho-kinetic signature of a second embryo with an unknown classification, wherein the second morpho-kinetic signature is a representation of morpho-kinetic events in the second embryo as a function of time;
• inputting, using the control circuitry, the second morpho-kinetic signature into the trained artificial neural network;
• and
• receiving, using the control circuitry, a prediction from the trained artificial neural network that the second morpho-kinetic signature corresponds to the known classification.

A system for classifying morpho-kinetic signatures in embryos, the system comprising:

• memory configured to store an artificial neural network;
• and
• control circuitry configured to:
• receive a first morpho-kinetic signature of a first embryo, wherein the first morpho-kinetic signature is a representation of morpho-kinetic events in the first embryo as a function of time;
• label the first morpho-kinetic signature with a known classification;
• train the artificial neural network to detect the known classification based on the first morpho-kinetic signature;
• receive a second morpho-kinetic signature of a second embryo with an unknown classification, wherein the second morpho-kinetic signature is a representation of morpho-kinetic events in the second embryo as a function of time;
• input the second morpho-kinetic signature into the trained artificial neural network;
• and
• receive a prediction from the trained artificial neural network that the second morpho-kinetic signature corresponds to the known classification.

A non-transitory computer-readable medium for classifying morpho-kinetic signatures in embryos comprising instructions that, when executed by one or more processors, cause operations comprising:

• receiving a first morpho-kinetic signature of a first embryo, wherein the first morpho-kinetic signature is a representation of morpho-kinetic events in the first embryo as a function of time;
• labeling the first morpho-kinetic signature with a known classification;
• training an artificial neural network to detect the known classification based on the first morpho-kinetic signature;
• receiving a second morpho-kinetic signature of a second embryo with an unknown classification, wherein the second morpho-kinetic signature is a representation of morpho-kinetic events in the second embryo as a function of time;
• inputting the second morpho-kinetic signature into the trained artificial neural network;
• and
• receiving a prediction from the trained artificial neural network that the second morpho-kinetic signature corresponds to the known classification.