Integrating deep learning in public health: a novel approach to PICC-RVT risk assessment.

Variable selection Through statistical analysis, we found that factors such as gender, age, height, education, primary diagnosis upon admission, activated partial prothrombin time, albumin, method of catheter fixation, type of pre-filled sealing fluid, type of connector, catheter opening, type of dressing, and certain chemotherapy drugs (such as platinum, anthracyclines, alkylating agents, and plant alkaloids) exhibited highly significant statistical differences ( p < 0.001).

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