A.I and Machine Learning Based Risk Prediction Model to Improve the Clinical Management of Endometrial Cancer.

Summary

Prediction of preoperative endometrial biopsy: the evolution from hyperplasia to cancer, the prognosis and the risk of recurrence. Intelligence methods artificial risk will be used to redefine the current risk classes including our profile immuno-mutational to provide a more precise characterization and closer to the real prognosis of the patient.

Eligibility

Inclusion Criteria:

* Age \> 18 years;
* Histological diagnosis of endometrial hyperplasia, endometrioid adenocarcinoma of the endometrium, healthy endometrium in patients undergoing total hysterectomy for benign extra-endometrial disease;
* Written informed consent (to the study and data processing), for the party's patients only prospective and/or in follow-up) For the retrospective cohort: availability of samples adequately stored at the biobank of the Institute and availability of data relating to follow-up (at least 2 years)

Exclusion Criteria:

All exclusion criteria adopted in the surgical protocols will be applied to the study. In particular:

* Comorbidities not controlled with adequate medical therapy;
* Infections of the endometrial cavity (pyometra);
* Synchronous cancer;
* Neoadjuvant treatments;
* Previous radiotherapy treatments of the pelvic region;
* Hormone therapies.

Conditions2

Browse More Trials