Systems and methods for controlling a surgical pump using endoscopic video data

A system for controlling a fluid pump for use in surgical procedures, the system comprising:

• a memory;
• one or more processors;
• wherein the memory stores one or more programs that when executed by the one or more processors, cause the one or more processors to:
• receive video data captured from an imaging tool configured to image an internal portion of a patient;
• apply one or more machine learning classifiers to the received video data to generate one or more classification metrics based on the received video data, wherein the one or more machine learning classifiers are created using a supervised training process that comprises using one or more annotated images to train the machine learning classifier;
• determine the presence of one or more conditions in the received video data based on the generated one or more classification metrics;
• and
• adjust the flow through or head pressure from the fluid pump based on the determined presence of the one or more conditions in the received video data.

A non-transitory computer readable storage medium storing one or more programs for controlling a fluid pump for use in surgical procedures, for execution by one or more processors of an electronic device that when executed by the device, cause the device to:

• receive video data captured from an imaging tool configured to image an internal portion of a patient;
• apply one or more machine learning classifiers to the received video data to generate one or more classification metrics based on the received video data, wherein the one or more machine learning classifiers are created using a supervised training process that comprises using one or more annotated images to train the machine learning classifier;
• determine the presence of one or more conditions in the received video data based on the generated one or more classification metrics;
• and
• adjust the flow through or head pressure from the fluid pump based on the determined presence of the one or more conditions in the received video data.