We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Category ‐ Gynae Oncology.
- Abstract
Required variables will include patient age, parity, body mass index, ethnicity, medical comorbidities, preoperative disease characteristics (tumor size, extent of myometrial invasion, parametrial, cervical and vaginal involvement, iliac and paraaortic lymph node involvement, omental/peritoneal involvement, distant metastasis), staging, histopathology (histological type, grading, lymph vascular space invasion), family and personal history of cancer, treatment approach (surgical management including lymphadenectomy, brachytherapy, external pelvic radiation, chemotherapy, and hormonal therapy). Therefore, physicians should be more aware of patients' rights regarding the disclosure of gynecological cancer diagnosis despite patients' age, and the importance of informing the patients about their health should be explained to families. B Methods: b Prospective consecutive identification of patients with malignant or premalignant disease of vulva from our central tertiary cancer centre multidisciplinary team meetings between 06/03/2020 - 26/03/2021, with collection of data pertaining to patient demography, perioperative care and outcomes, from patient medical records. PP.0066 Endometrial cancer prediction model: A machine learning-based prognostic scoring system (Prot... Sherif Shazly I Leeds Teaching Hospitals, Leeds, UK i B Objective b : To create a predictive model of endometrial cancer prognosis that considers patient and disease characteristics using machine learning approach, and to facilitate individualization of management by predicting the impact of presumed treatment plans on a specific patient survival.
- Publication
BJOG: An International Journal of Obstetrics & Gynaecology, 2022, Vol 129, p36
- ISSN
1470-0328
- Publication type
Academic Journal
- DOI
10.1111/1471-0528.7_17178