January 2026 in “Open Science Framework” This scoping review systematically maps the use of AI and ML in alopecia research, highlighting the evolution from diagnostic tools to more advanced prognostic frameworks. It identifies the dominance of CNNs for image-based diagnosis, limited multimodal integration, and a lack of prognostic or causal modeling. Key gaps include the need for generative prognosis frameworks, fairness evaluations, privacy-aware systems, and treatment-response prediction. The review provides a taxonomy of AI approaches, visual aids, and recommendations for future research, emphasizing the development of equitable AI tools for personalized prognosis and treatment planning in alopecia care.
2 citations
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October 2023 in “Cancer Reports” Mitochondrial features can predict colorectal cancer outcomes and improve immunotherapy.
37 citations
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November 2017 in “Medical Sciences” Melanoma's complexity requires personalized treatments due to key genetic mutations and tumor-initiating cells.
11 citations
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September 2024 in “Journal of Advanced Research” 3D-bioprinting models of pancreatic cancer could help personalize treatments but need more testing.
21 citations
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March 2019 in “Critical Reviews in Clinical Laboratory Sciences” The androgen receptor is a promising target for breast cancer treatment, especially in triple-negative cases, but more research is needed for personalized therapies.