Finding the combination of multiple biomarkers to diagnose oral squamous cell carcinoma – A data mining approach

Artificial intelligence in salivary biomarker discovery and validation for oral diseases

“…With the aim of biomarker discovery being to select optimal biomarkers or develop robust biomarker platforms to be employed in downstream analyses, the workflow for analyzing the outputs of multi-omics analyses in saliva samples during biomarker discovery is presented in Figure 1. In one framework, plots, spectra, gel photos, blots, and images that represent raw outputs of high-throughput technologies may be processed for comparative bioinformatics or statistical analysis to generate structured data as is the usual prac- Taxonomic profile 16S rRNA sequencing Classification Random forest da Costa et al, 2022;Song et al, 2020;Torres & Judson-Torres, 2019). However, it is often best to compare different feature selection approaches to determine whether concordance in the biomarkers selected exists.…”

“…Utilizing AI algorithms with salivary biomarkers to generate models that can be validated and applied potentially in clinical practice is more common than its use for biomarker discovery (Arias-Bujanda et al, 2020;Banavar et al, 2021;Bostanci et al, 2018;Carnielli et al, 2018;da Costa et al, 2022;de Dumast et al, 2018;Eriksson et al, 2022;Gomez Hernandez et al, 2021;Grier et al, 2021;Kim et al, 2021;Kistenev et al, 2018;Koller et al, 2021;Koopaie et al, 2021;Kouznetsova et al, 2021;Lee et al, 2021;Liu, Tong, et al, 2021;Lyashenko et al, 2020;Monedeiro et al, 2021;Nakano et al, 2014Nakano et al, , 2018Pang et al, 2021;Schulte et al, 2020;Shoukri et al, 2019;Song et al, 2020;Sonis et al, 2013;Tamaki et al, 2009;Winck et al, 2015;Wu et al, 2021;Zhang et al, 2021;Zhou et al, 2021;Zlotogorski-Hurvitz et al, 2019) AI-based biomarker platforms constructed during biomarker discovery may be executed for biomarker validation on the premise that each additional saliva sample would be subjected to similar large-scale analysis and used as input for the same models (Adeoye, Wan, et al, 2022). While this may not be cost-effective, feasible, or encourage validation, promising biomarkers selected using conventional statistical approaches or AI-based exploratory analysis (in biomarker discovery) may be used to develop new models for biomarker validation and potential clinical application (Koopaie et al, 2021;Tamaki et al, 2009).…”

Sağlıkta veri kalitesi ve veri madenciliği uygulamaları

“…Costa ve diğerleri, çoklu biyobelirteçlerin kombinasyonu ile oral skuamöz hücreli karsinom teşhisi koymak için bir veri madenciliği yaklaşımı ortaya koymuştur [30]. Çalışmada tükürük örnekleri, cinsiyet, yaş ve sigara alışkanlığı gibi kriterler rastgele orman algoritması ile kullanılmıştır.…”

“…Çalışma %80'in üzerinde doğruluk vermiştir. Bu çalışma doğru oral skuamöz hücreli karsinom teşhisi koymak için kullanılabilecektir [30].…”

Early Diagnosis and Diagnostic Delay in Oral Cancer

“…Beyond any doubt, delays in the diagnosis of oral cancers would be diminished by the identification of specific diagnostic markers. The quest for these molecules is intense, from a range of approaches [ 15 , 16 ], with interesting potential candidates. In the same line, tissue markers exposing early phases of malignant transformation can also contribute to this goal.…”