Digital phenotyping in clinical nursing is systematically reviewed from four dimensions:symptom monitoring and early identification, risk prediction and decision support, personalized intervention and self-management support, and remote follow-up and transitional care. This review elucidates the clinical value of digital phenotyping in symptom surveillance, risk stratification, individualized intervention, and remote follow-up. It points out that the application of digital phenotyping faces challenges including technological standardization, and integration with clinical information systems. Finally, future directions are proposed, such as developing nurse-oriented visual decision-support systems, advancing multimodal data fusion, and promoting the effective integration of just-in-time adaptive interventions with digital phenotyping, with the aim of providing evidence to inform localized application and innovative development of digital phenotyping in the field of clinical nursing.