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Deep phenotyping, the systematic, quantitative assessment of macro- and micro-level phenotypes, is pivotal to precision medicine. Although genomics has advanced rapidly, incomplete phenotypic data limit medical insights and research. This review starts from tracing the evolution of deep phenotyping, highlighting standardized terminologies (HPO), advanced technologies (wearable sensors, imaging, PheWAS, AI-assisted methods), procedural frameworks, and large-scale databases. By integrating these resources, deep phenotyping clarifies disease heterogeneity, refines genotype–phenotype correlations, and identifies novel biomarkers—enhancing diagnostic accuracy via phenotype-driven approaches and reanalysis. Moreover, deep phenotyping underpins precision medicine by enabling robust disease stratification, personalized clinical care, and biomarker-driven trials. Besides these, it aids disease prevention, refines prognostic prediction, and supports lifespan-based strategies from pregnancy to aging. Emerging fields such as xenotransplantation illustrate its capacity to achieve precision medicine. We also introduce global perspectives on implementing deep phenotyping across diverse settings, illustrating its adaptability and clinical impact. Finally, we propose a flexible, three-module strategy integrating study scope, data acquisition, and analytic methods to guide future research of deep phenotyping. This review underscores deep phenotyping’s transformative potential to elevate diagnostics, inform targeted therapies, and optimize patient outcomes, heralding a new era in medical genetics and genomics.
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Li et al. (2026) studied this question.
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