## 5 Discussion and Conclusions  
Modern medicine and dentistry require the growing support of digital technologies to improve the diagnostic, therapeutic, and follow-up processes in patient management, including and especially cancer patients, where the timeliness and precocity of diagnosis and intervention, and knowledge of the prognosis related to novel parameters, can make the difference between life and death.  
Digital aid is conveyed by the practice of eHealth, recently regulated by the World Health Organization [48].  
One such innovative approach to oral health-related challenges in oral oncology is fractal analysis to assess quantitatively the regularity/irregularity of patterns mathematically and digitally in healthy mucosa compared with OC and OPMDs.  
The present review affirmatively answered whether fractal analysis could be considered a valid support method to diagnose oral cancer or its precursors in humans.  
Indeed, fractal analysis succeeded in the measurement and quantification of changes in the morphological complexity of the epithelial, connective, and vascular components of the tumor.  
In detail, the box-counting method was the most frequently used. However, it was possible to assist, year after year, in the refinement of the method and the increasing support of digital processes for image analysis, from conventional photographs scanned and manually segmented up to the acquisition through CDD cameras and integrated software, thus resulting in more accurate and standardized textural analyses.  
The keratinocyte nuclear boundary was the most frequently considered and most significative fractal object. The mean nuclear fractal dimension (nFD) progressively increased from healthy oral keratinocytes to those from poorly differentiated OC, thus being considered an independent prognostic factor of survival in oral cancer patients. Furthermore, the nFD prognostic significance was enhanced when grading, immune infiltration, and tumoral neovascularization were correlated.  
Other works focused on this last feature, the pattern of tumor-associated neovascularization, thus reporting statistically significant differences between the vascular density of OC compared with healthy mucosa.  
A third most frequent fractal object was the epithelial-subepithelial interface, whose FD statistically significantly differed between healthy mucosa and OC and between healthy mucosa and OPMDs.  
Last, the fractal analyses failed in some works, such as those on solar chemilis. In these cases, it was unclear whether the failure to discriminate was due to the fractal object considered (a clinical picture) or to the pathological features not adequately investigated through fractal analysis.  
Furthermore, few works--only 27--have emerged from the literature. They are very heterogeneous, considering the source analyzed (mainly clinical pictures or histological specimens), the diseases investigated, the methodologies of fractal analysis, and the significance of the results.  
These limitations are mainly related to the preliminary nature of these works, which, although pioneering, need more extended and standardized studies to be consolidated and considered for clinical applications.