The present invention relates to a system for the automatic diagnosis of uterine cervical cancer, wherein the system classifies and machine-learns uterine cervix data, necessary for automatically diagnosing uterine cervical cancer, according to accurate criteria, and automatically diagnoses uterine cervical cancer on the basis of the machine learning. The system is characterized by including: a training data generation unit which, in a learning mode, classifies unclassified captured image data on the uterine cervix, transmitted from an external device or a storage unit, according to a multi-stage combination of classification criteria, and generates new training data for each classification criterion; a captured image preprocessing unit which pre-processes captured uterine cervix images; auterine cervical cancer diagnosis unit including a machine-learning model which is for uterine cervical cancer and learns features of the training data generated for each classification criterion inthe learning mode, wherein, in a diagnosis mode, the machine-learning model generates, for the captured and pre-processed uterine cervix image, diagnosis information about whether uterine cervical cancer has developed; a screen display control unit which displays the diagnosis information, and displays and outputs a user interface screen through which evaluation information can be input by a radiologist; a re-training data generation unit which extracts information necessary for re-training from the evaluation information input through the user interface screen, and requests re-training of themachine-learning model; and a diagnosis and evaluation information storage unit which stores the diagnosis information about whether uterine cervical cancer has developed, and the evaluation information input through the user interface screen.
SYSTEM FOR AUTOMATIC DIAGNOSIS OF UTERINE CERVICAL CANCER