# Digital technologies in psoriasis management: from precision diagnosis to therapeutic innovation and holistic care

## TL;DR

Digital technologies are improving psoriasis care by enabling more accurate diagnosis, personalized treatment, and better long-term monitoring.

## Contribution

The paper introduces a precision-based framework using AI and IoT to enhance psoriasis diagnosis, treatment, and rehabilitation.

## Key findings

- An AI-integrated dermoscopy model achieves 92.3% accuracy in diagnosing psoriasis, outperforming dermatologists.
- AI-assisted biologic selection increases complete clearance rates to 61% with fewer adverse events.
- IoT-enabled monitoring systems improve self-management and adaptive interventions for psoriasis patients.

## Abstract

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.