Yazar "Wilder-Smith, P." seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    Improving Oral Cancer Outcomes with Imaging and Artificial Intelligence
    (SAGE Publications Inc., 2020) Ilhan, B.; Lin, K.; Guneri, P.; Wilder-Smith, P.
    Early diagnosis is the most important determinant of oral and oropharyngeal squamous cell carcinoma (OPSCC) outcomes, yet most of these cancers are detected late, when outcomes are poor. Typically, nonspecialists such as dentists screen for oral cancer risk, and then they refer high-risk patients to specialists for biopsy-based diagnosis. Because the clinical appearance of oral mucosal lesions is not an adequate indicator of their diagnosis, status, or risk level, this initial triage process is inaccurate, with poor sensitivity and specificity. The objective of this study is to provide an overview of emerging optical imaging modalities and novel artificial intelligence–based approaches, as well as to evaluate their individual and combined utility and implications for improving oral cancer detection and outcomes. The principles of image-based approaches to detecting oral cancer are placed within the context of clinical needs and parameters. A brief overview of artificial intelligence approaches and algorithms is presented, and studies that use these 2 approaches singly and together are cited and evaluated. In recent years, a range of novel imaging modalities has been investigated for their applicability to improving oral cancer outcomes, yet none of them have found widespread adoption or significantly affected clinical practice or outcomes. Artificial intelligence approaches are beginning to have considerable impact in improving diagnostic accuracy in some fields of medicine, but to date, only limited studies apply to oral cancer. These studies demonstrate that artificial intelligence approaches combined with imaging can have considerable impact on oral cancer outcomes, with applications ranging from low-cost screening with smartphone-based probes to algorithm-guided detection of oral lesion heterogeneity and margins using optical coherence tomography. Combined imaging and artificial intelligence approaches can improve oral cancer outcomes through improved detection and diagnosis. © International & American Associations for Dental Research 2020.
  • Küçük Resim Yok
    Öğe
    Real-Time PCR Detection of Candida Species in Biopsy Samples from Non-Smokers with Oral Dysplasia and Oral Squamous Cell Cancer: A Retrospective Archive Study
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023) İlhan, B.; Vural, C.; Gürhan, C.; Vural, C.; Veral, A.; Wilder-Smith, P.; Özdemir, G.
    The impact of Candida sp. in the development of oral cancer remains uncertain and requires sensitive analytical approaches for clarification. Given the invasive capabilities of these microorganisms in penetrating and invading host tissues through hyphal invasion, this study sought to detect the presence of five Candida sp. in oral biopsy tissue samples from non-smoker patients. Samples were obtained from patients at varying stages of oral carcinogenesis, including dysplasia, carcinoma in situ, OSCC, and histologically benign lesions, and analyzed using Real-Time PCR. Oral tissue samples from 80 patients (46 males and 34 females) were included. Significantly higher C. albicans presence was detected in the mild/moderate dysplasia group compared to the healthy (p = 0.001), carcinoma in situ (p = 0.031) and OSCC groups (p = 0.000). Similarly, C. tropicalis carriage was higher in tissues with mild/moderate dysplasia compared to healthy (p = 0.004) and carcinoma in situ (p = 0.019). Our results showed a significant increase in the presence of C. albicans and C. tropicalis within the mild/moderate dysplasia group compared to other cohorts. Coexistence of these two microorganisms was observed, suggesting a potential transition from a commensal state to an opportunistic pathogen, which could be particularly linked to the onset of oral neoplasia. © 2023 by the authors.