Background/Objectives: Radiomics-based machine learning models have demonstrated high accuracy in differentiating benign from malignant orbital masses, with early studies suggesting performance comparable to expert radiologists. However, translation into clinical practice remains limited due to dataset constraints, including retrospective study designs, single-center cohorts, and underrepresentation of diverse patient populations. This review aims to evaluate the current evidence supporting radiomics in orbital disease while critically examining barriers to generalizability and equity across ophthalmology, otolaryngology, and plastic surgery. Methods: A narrative literature review was conducted to assess radiomics applications in orbital oncology and reconstruction. Studies evaluating diagnostic accuracy, margin assessment, postoperative surveillance, and surgical planning across ophthalmology, head and neck surgery, and reconstructive surgery were analyzed, with particular attention paid to dataset composition, validation strategies, and imaging standardization. Results: Radiomics models demonstrated high diagnostic performance in differentiating orbital tumors, optimizing surgical planning, and aiding postoperative monitoring. However, most studies relied on small, homogeneous datasets lacking racial, ethnic, and pediatric representation. External validation was uncommon, and imaging heterogeneity limited reproducibility. These deficiencies restrict the clinical translation of radiomics and risk exacerbating healthcare disparities, particularly among underrepresented populations. Conclusions: Radiomics holds promise as a precision medicine tool for orbital diagnosis, surgical navigation, and postoperative care. Nevertheless, its clinical adoption is constrained by dataset bias, lack of standardization, and limited prospective validation. Future progress requires multi-institutional, demographically diverse datasets and standardized imaging protocols to ensure equitable and generalizable implementation across specialties.

Introduction: Systemic autoimmune diseases frequently involve both the skin and eyes, with early cutaneous manifestations often serving as visible indicators of deeper, multisystem pathology. Conditions such as systemic lupus erythematosus, dermatomyositis, sarcoidosis, and Sjögren’s syndrome display characteristic skin findings, including malar rash, heliotrope eruption, lupus pernio, or xerosis, which may precede or parallel serious ocular complications, including uveitis, retinal vasculitis, conjunctival granulomas, and keratoconjunctivitis sicca. Despite this overlap, diagnostic and therapeutic strategies remain fragmented across specialties. Objectives: By highlighting the clinical intersections between dermatological and ocular manifestations in systemic autoimmune diseases, we aim to promote earlier recognition, integrated treatment, and improved outcomes for patients affected by these multisystem disorders. Methods: This review synthesizes the literature from the last fifteen years, between 2010 and 2025, on four major autoimmune conditions: systemic lupus erythematosus, dermatomyositis, sarcoidosis, and Sjögren’s syndrome. Results: We examine disease-specific immunopathology, diagnostic modalities, and therapeutic strategies, while also discussing the need for interdisciplinary management models, including those that bridge dermatology and ophthalmology. Conclusion: By highlighting these clinical intersections, we aim to promote earlier recognition, integrated treatment, and improved outcomes for patients affected by these multisystem disorders.