Background: In recent years, Artificial Intelligence (AI) has shown transformative potential in advancing breast cancer care globally. This scoping review seeks to provide a comprehensive overview of AI applications in breast cancer care, examining how they could reshape diagnosis, treatment, and management on a worldwide scale and discussing both the benefits and challenges associated with their adoption. Methods: In accordance with PRISMA-ScR and ensuing guidelines on scoping reviews, PubMed, Web of Science, Cochrane Library, and Embase were systematically searched from inception to end of May 2024. Keywords included “Artificial Intelligence” and “Breast Cancer”. Original studies were included based on their focus on AI applications in breast cancer care and narrative synthesis was employed for data extraction and interpretation, with the findings organized into coherent themes. Results: Finally, 84 articles were included. The majority were conducted in developed countries (n = 54). The majority of publications were in the last 10 years (n = 83). The six main themes for AI applications were AI for breast cancer screening (n = 32), AI for image detection of nodal status (n = 7), AI-assisted histopathology (n = 8), AI in assessing post-neoadjuvant chemotherapy (NACT) response (n = 23), AI in breast cancer margin assessment (n = 5), and AI as a clinical decision support tool (n = 9). AI has been used as clinical decision support tools to augment treatment decisions for breast cancer and in multidisciplinary tumor board settings. Overall, AI applications demonstrated improved accuracy and efficiency; however, most articles did not report patient-centric clinical outcomes. Conclusions: AI applications in breast cancer care show promise in enhancing diagnostic accuracy and treatment planning. However, persistent challenges in AI adoption, such as data quality, algorithm transparency, and resource disparities, must be addressed to advance the field.

Background: The risk of skin cancer is determined by environmental factors like ultraviolet radiation (UVR), personal habits like time spent outdoors and genetic factors. This review aimed to survey existing studies in gene–environment (GxE) interaction on skin cancer risk, and report on GxE effect estimates.Methods: We searched Embase, Medline (Ovid) and Web of Science (Core Collection) and included only primary research that reported on GxE on the risk of the three most common types of skin cancer: basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and melanoma. Quality assessment followed the Newcastle–Ottawa Scale. Meta‐analysis was not possible because no two studies examined the same interaction. This review was registered on PROSPERO (CRD42021238064).Results: In total 260 records were identified after exclusion of duplicates. Fifteen studies were included in the final synthesis—12 used candidate gene approach. We found some evidence of GxE interactions with sun exposure, notably, with MC1R, CAT and NOS1 genes in melanoma, HAL and IL23A in BCC and HAL and XRCC1 in SCC.Conclusion: Sun exposure seems to interact with genes involved in pigmentation, oxidative stress and immunosuppression, indicating that excessive UV exposure might exhaust oxidative defence and repair systems differentially, dependent on genetic make‐up. Further research is warranted to better understand skin cancer epidemiology and develop sun exposure recommendations. A genome‐wide approach is recommended as it might uncover unknown disease pathways dependent on UV radiation.

Background/Objectives: Synchronous ipsilateral supraclavicular lymph node metastases (sISLMs) in breast cancer are rare and associated with poor prognosis. The optimal locoregional treatment strategy remains unclear, particularly regarding the role of supraclavicular lymph node dissection (SLND). Methods: We conducted a systematic review and network meta-analysis, including studies published up to end December 2023, to compare the outcomes of SLND combined with radiotherapy (RT) and systemic therapy (ST), SLND with ST alone, and ST alone, using RT + ST as the reference. Results: Ten studies involving 3346 patients were included for overall survival (OS) analysis, and six studies were included for disease-free survival (DFS). SLND + RT + ST showed similar OS and DFS compared to RT + ST. Sensitivity analyses revealed that SLND limited to level V improved OS (HR: 0.47, 95% CI: 0.29–0.77), while more extensive dissections (level V+) worsened outcomes (HR: 1.41, 95% CI: 1.10–1.80). Conclusions: These findings suggest that selective SLND may benefit certain patients, but broader application should be approached with caution pending results from future randomized trials.