Progress in the application of multimodal artificial intelligence in early identification and nursing of pressure injuries in dark-skinned populations

doi:10.3761/j.issn.0254-1769.2026.15.019

Abstract

Abstract:

Affected by congenital genetic factors，individuals with dark skin exhibit high epidermal melanin deposition，which easily obscures early erythema signs of pressure injuries. Multimodal artificial intelligence integrates multi-source data，including medical images，physiological signals and clinical texts. It adopts data fusion algorithms to extract multidimensional complementary information，thereby breaking through the limitations of conventional single visual assessment. It provides objective and innovative insights for the early accurate identification，dynamic risk early warning，and personalized nursing decision-making of pressure injuries in dark-skinned populations. This article reviews the clinical assessment dilemmas of pressure injuries in dark-skinned groups，elaborates on the data fusion principles and application strategies of multimodal artificial intelligence，and summarizes its research progress in nursing practice. Meanwhile，it thoroughly analyzes key challenges in the clinical translation of this technology，such as data bias，insufficient clinical adaptability，and privacy and ethical constraints. The study aims to offer theoretical references for establishing a safe and efficient human-machine collaborative nursing model，optimizing the prevention and control system of pressure injuries，and improving the quality of specialized nursing.

Key words: Multimodality, Artificial Intelligence, Data Fusion, Dark Skin Tones, Pressure Injury, Nursing Care, Review

摘要：

深肤色患者受先天遗传因素影响，表皮黑色素沉积水平较高，易遮蔽压力性损伤早期红斑体征。多模态人工智能技术通过整合影像学图像、生理信号及临床文本等多源数据，依托数据融合算法挖掘多维度互补信息，有效突破传统单一视觉评估的局限，为深肤色患者压力性损伤的早期精准识别、动态风险预警及个性化护理决策提供了新思路。该文综述深肤色患者压力性损伤的临床评估困境、多模态人工智能的数据融合原理与应用策略及其在护理实践中的研究进展，深入分析该技术临床转化过程中存在的数据偏倚、临床适配不足、隐私伦理约束等关键问题，旨在为构建安全高效的人机协同护理模式、优化压力性损伤防控体系、提升专科护理质量提供参考。

关键词: 多模态, 人工智能, 数据融合, 深肤色, 压力性损伤, 护理, 综述

LOU Jie, HUANG Rongrong, XIE Yusheng, LIU Zhaoqing, NIE Pu, HE Kehuan, WANG Langxun. Progress in the application of multimodal artificial intelligence in early identification and nursing of pressure injuries in dark-skinned populations[J]. Chinese Journal of Nursing, 2026, 61(15): 2155-2160.

娄洁, 黄蓉蓉, 谢玉生, 刘昭晴, 聂璞, 何可欢, 王浪薰. 多模态人工智能在深肤色患者压力性损伤早期识别与护理中的研究进展[J]. 中华护理杂志, 2026, 61(15): 2155-2160.

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