The lancet oncology
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The lancet oncology · Nov 2024
Review Practice GuidelineFertility-sparing treatment and follow-up in patients with cervical cancer, ovarian cancer, and borderline ovarian tumours: guidelines from ESGO, ESHRE, and ESGE.
The European Society of Gynaecological Oncology, the European Society of Human Reproduction and Embryology, and the European Society for Gynaecological Endoscopy jointly developed clinically relevant and evidence-based guidelines focusing on key aspects of fertility-sparing strategies and follow-up of patients with cervical cancers, ovarian cancers, and borderline ovarian tumours. The developmental process of these guidelines is based on a systematic literature review and critical appraisal involving an international multidisciplinary development group consisting of 25 experts from relevant disciplines (ie, gynaecological oncology, oncofertility, reproductive surgery, endoscopy, imaging, conservative surgery, medical oncology, and histopathology). Before publication, the guidelines were reviewed by 121 independent international practitioners in cancer care delivery and patient representatives. The guidelines comprehensively cover oncological aspects of fertility-sparing strategies during the initial management, optimisation of fertility results and infertility management, and the patient's desire for future pregnancy and beyond.
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The lancet oncology · Nov 2024
ReviewArtificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements.
The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed.
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The lancet oncology · Nov 2024
ReviewArtificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice.
Technological advancements have enabled the extended investigation, development, and application of computational approaches in various domains, including health care. A burgeoning number of diagnostic, predictive, prognostic, and monitoring biomarkers are continuously being explored to improve clinical decision making in neuro-oncology. These advancements describe the increasing incorporation of artificial intelligence (AI) algorithms, including the use of radiomics. ⋯ To this end, we investigate the repeatability, reproducibility, and stability of AI in response assessment in neuro-oncology in studies on factors affecting such computational approaches, and in publicly available open-source data and computational software tools facilitating these goals. The pathway for standardisation and validation of these approaches is discussed with the view of trustworthy AI enabling the next generation of clinical trials. We conclude with an outlook on the future of AI-enabled neuro-oncology.