Digital Technologies in Psoriasis Management: From Precision Diagnosis to Therapeutic Innovation and Holistic Care

Zhenni Gong¹Chen Yusheng¹Wei Xi¹Yicheng Zhang²Weihao Cheng²Sun Tao²Liang Su¹Xue Wang^1*

• ¹The First Affiliated Hospital of Shihezi University, Shihezi, China
• ²Shihezi University School of Medicine, Shihezi, China

Psoriasis, an enduring systemic inflammatory dermatological condition with rising global incidence, presents significant impediments to conventional diagnostic and therapeutic strategies, primarily due to the reliance on subjective evaluation methods, notable adverse effects of treatments, and suboptimal long-term patient adherence. This narrative review systematically explores how digital innovations are transforming its comprehensive management. Digital innovations are transforming its comprehensive management: In diagnosis, artificial intelligence (AI)-integrated dermoscopy (EfficientNet-B4 model) achieves a 92.3% accuracy in differentiating psoriasis from other papulosquamous disorders, surpassing 230 dermatologists (86.7% accuracy) and enhancing severity assessment through deep learning, thereby mitigating subjective bias. In treatment, smart phototherapy devices refine dosage optimization through algorithmic processes, while AI-assisted biologic selection elevates complete clearance rates from 39% to 61% (compared to traditional protocols) with severe adverse events diminishing to less than 2%. In rehabilitation, Internet of things (IoT)-enabled monitoring systems assimilate real-time data through wearable technology and digital platforms to enhance self-management and adaptive intervention strategies. Multi-omics data integration and computational drug design expedite the development of novel therapies. Nevertheless, challenges such as inadequate data standardization, privacy issues, restricted algorithmic transparency, and lack of prolonged validation remain. Digital technologies are reconfiguring psoriasis management from diagnosis (objective imaging) to treatment (personalized dose management) and rehabilitation (IoT-enabled monitoring), establishing a precision-based, data-centric framework.