AI-powered advances in type II endometrial cancer: global trends and African contexts

IntroductionThe advent of artificial intelligence (AI) in oncology has opened new avenues for enhancing the diagnosis, treatment, and prognosis of type II endometrial cancers (ECs), which account for the majority of EC-related deaths globally. With rising incidence and increasing concerns in Africa,...

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Main Authors: Thulo Molefi, Lloyd Mabonga, Rodney Hull, Motshedisi Sebitloane, Zodwa Dlamini
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Oncology
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Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1581645/full
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author Thulo Molefi
Thulo Molefi
Thulo Molefi
Lloyd Mabonga
Rodney Hull
Motshedisi Sebitloane
Zodwa Dlamini
author_facet Thulo Molefi
Thulo Molefi
Thulo Molefi
Lloyd Mabonga
Rodney Hull
Motshedisi Sebitloane
Zodwa Dlamini
author_sort Thulo Molefi
collection DOAJ
description IntroductionThe advent of artificial intelligence (AI) in oncology has opened new avenues for enhancing the diagnosis, treatment, and prognosis of type II endometrial cancers (ECs), which account for the majority of EC-related deaths globally. With rising incidence and increasing concerns in Africa, type II ECs are often detected in advanced stages, exhibit aggressive progression, and resist conventional therapies. Despite these characteristics, they are still treated similarly to type I ECs, which are less aggressive and more treatment-responsive. Currently, no specific targeted therapies exist for type II ECs, creating an urgent need for innovative treatment options.MethodsThis review examines the integration of AI-powered approaches in the care of type II ECs, focusing on their potential to address rising incidence and disparities in Africa. It explores AI-driven diagnostic tools, tailored therapeutic options, and ongoing innovative projects, including efforts to integrate indigenous knowledge into AI applications.ResultsAI-powered therapeutic options tailored to the unique clinical profiles of type II EC patients show promise for developing targeted therapies. Several innovative projects are underway, leveraging AI to meet Africa’s unique healthcare challenges. These applications demonstrate significant potential to reduce healthcare disparities and improve patient outcomes, especially in resource-limited settings.DiscussionThis review highlights the transformative potential of AI technologies in improving the diagnosis, treatment and management of type II ECs, particularly in Africa, where healthcare disparities are significant. Through the integration of AI in the type II EC care continuum, challenges in African healthcare can be overcome. Innovative projects, leveraging AI to meet the continent’s challenges, have the potential to improve patient outcomes. AI-driven therapies hold the key to personalized oncologic care, and indigenous African knowledge can be used to develop Afrocentric healthcare solutions. In Future, with continued research and the development of robust frameworks and transparent algorithms, investment and collaboration, the potential of AI in Type II EC will be realized.
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spelling doaj-art-e9642a6a38044c7fa6a2e4356f6726aa2025-08-20T03:50:05ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-07-011510.3389/fonc.2025.15816451581645AI-powered advances in type II endometrial cancer: global trends and African contextsThulo Molefi0Thulo Molefi1Thulo Molefi2Lloyd Mabonga3Rodney Hull4Motshedisi Sebitloane5Zodwa Dlamini6Discipline of Obstetrics and Gynaecology, School of Clinical Medicine, University of KwaZulu-Natal, Durban, South AfricaSAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Research Institute (PACRI), University of Pretoria, Pretoria, South AfricaDepartment of Medical Oncology, University of Pretoria, Pretoria, South AfricaSAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Research Institute (PACRI), University of Pretoria, Pretoria, South AfricaSAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Research Institute (PACRI), University of Pretoria, Pretoria, South AfricaDiscipline of Obstetrics and Gynaecology, School of Clinical Medicine, University of KwaZulu-Natal, Durban, South AfricaSAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Research Institute (PACRI), University of Pretoria, Pretoria, South AfricaIntroductionThe advent of artificial intelligence (AI) in oncology has opened new avenues for enhancing the diagnosis, treatment, and prognosis of type II endometrial cancers (ECs), which account for the majority of EC-related deaths globally. With rising incidence and increasing concerns in Africa, type II ECs are often detected in advanced stages, exhibit aggressive progression, and resist conventional therapies. Despite these characteristics, they are still treated similarly to type I ECs, which are less aggressive and more treatment-responsive. Currently, no specific targeted therapies exist for type II ECs, creating an urgent need for innovative treatment options.MethodsThis review examines the integration of AI-powered approaches in the care of type II ECs, focusing on their potential to address rising incidence and disparities in Africa. It explores AI-driven diagnostic tools, tailored therapeutic options, and ongoing innovative projects, including efforts to integrate indigenous knowledge into AI applications.ResultsAI-powered therapeutic options tailored to the unique clinical profiles of type II EC patients show promise for developing targeted therapies. Several innovative projects are underway, leveraging AI to meet Africa’s unique healthcare challenges. These applications demonstrate significant potential to reduce healthcare disparities and improve patient outcomes, especially in resource-limited settings.DiscussionThis review highlights the transformative potential of AI technologies in improving the diagnosis, treatment and management of type II ECs, particularly in Africa, where healthcare disparities are significant. Through the integration of AI in the type II EC care continuum, challenges in African healthcare can be overcome. Innovative projects, leveraging AI to meet the continent’s challenges, have the potential to improve patient outcomes. AI-driven therapies hold the key to personalized oncologic care, and indigenous African knowledge can be used to develop Afrocentric healthcare solutions. In Future, with continued research and the development of robust frameworks and transparent algorithms, investment and collaboration, the potential of AI in Type II EC will be realized.https://www.frontiersin.org/articles/10.3389/fonc.2025.1581645/fullartificial intelligenceType II endometrial cancerAfrican healthcarepersonalized medicinediagnosticstreatment planning
spellingShingle Thulo Molefi
Thulo Molefi
Thulo Molefi
Lloyd Mabonga
Rodney Hull
Motshedisi Sebitloane
Zodwa Dlamini
AI-powered advances in type II endometrial cancer: global trends and African contexts
Frontiers in Oncology
artificial intelligence
Type II endometrial cancer
African healthcare
personalized medicine
diagnostics
treatment planning
title AI-powered advances in type II endometrial cancer: global trends and African contexts
title_full AI-powered advances in type II endometrial cancer: global trends and African contexts
title_fullStr AI-powered advances in type II endometrial cancer: global trends and African contexts
title_full_unstemmed AI-powered advances in type II endometrial cancer: global trends and African contexts
title_short AI-powered advances in type II endometrial cancer: global trends and African contexts
title_sort ai powered advances in type ii endometrial cancer global trends and african contexts
topic artificial intelligence
Type II endometrial cancer
African healthcare
personalized medicine
diagnostics
treatment planning
url https://www.frontiersin.org/articles/10.3389/fonc.2025.1581645/full
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