Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2025, Номер unknown, С. 126390 - 126390
Опубликована: Май 1, 2025
Язык: Английский
Cancers, Год журнала: 2024, Номер 16(3), С. 608 - 608
Опубликована: Янв. 31, 2024
A systematic review and a meta-analysis is presented on published articles the malignant transformation of oral lichen planus (OLP) related conditions, which, based current evidence, updates an earlier by our research group that included publications until November 2018. In this updated study (Nov-2023) we searched MEDLINE, Embase, Web Science, Scopus. We evaluated methodological quality studies (QUIPS tool) carried out meta-analyses. The inclusion criteria were met 101 (38,083 patients), 20 new primary-level (11,512 patients) in last 5 years added to study. pooled ratio was 1.43% (95% CI = 1.09-1.80) for OLP; 1.38% 0.16-3.38) lichenoid lesions; 1.20% 0.00-4.25) reactions; 5.13% 1.90-9.43) OLP with dysplasia. No significant differences found between OLL or LR groups subgroup (
Язык: Английский
Процитировано
23
Healthcare Analytics, Год журнала: 2023, Номер 3, С. 100199 - 100199
Опубликована: Май 22, 2023
Early detection is essential to effectively treat two of the most prevalent cancers, skin and oral. Deep learning approaches have demonstrated promising results in detecting these cancers using Computer-Aided Cancer Detection (CAD) medical imagery. This study proposes a deep learning-based method for oral cancer images. We discuss various Convolutional Neural Network (CNN) models such as AlexNet, VGGNet, Inception, ResNet, DenseNet, Graph (GNN). Image processing techniques image resizing filtering are applied images improve quality remove noise from Data augmentation used next expand training dataset strengthen robustness CNN model. The best model selected based on accuracy, loss, validation loss. shows DenseNet achieves state-of-the-art performance dataset.
Язык: Английский
Процитировано
32
Cancers, Год журнала: 2023, Номер 15(13), С. 3270 - 3270
Опубликована: Июнь 21, 2023
Oral and oropharyngeal cancers are a growing problem, accounting for 377,713 98,412 new cases per year all over the world 177,757 48,143 deaths annually, respectively. Despite substantial improvement in diagnostic procedures treatment techniques recent years, mortality rate has not decreased substantially last 40 which is still close to 50% of cases. The major cause responsible this high associated with percentage oral diagnosed advanced stages (stages III IV) where harbors poor efficacy, resulting challenges, mutilations, or disability. main reason cancer be at an stage delay, so it critical reduce delay order improve prognosis patients suffering from cancer. causes complex concern patients, healthcare professionals, services. In manuscript, critically reviewed based on current evidence, as well their causes, problems, potential strategies.
Язык: Английский
Процитировано
29
International Journal of Medical Sciences, Год журнала: 2024, Номер 21(6), С. 1165 - 1175
Опубликована: Янв. 1, 2024
Oral cancer is the most heterogeneous at clinical and histological levels.PI3K/AKT/mTOR pathway was identified as one of commonly modulated signals in oral cancer, which regulates major cellular metabolic activity cell.Thus, various proteins PI3K/AKT/mTOR were used therapeutic targets for to design more specific drugs with less off-target toxicity.This review sheds light on regulation PI3K/AKT/mTOR, its role controlling autophagy associated apoptosis during progression metastasis squamous type malignancy (OSCC).In addition, we reviewed detail upstream activators downstream effectors signaling potential treatment.
Язык: Английский
Процитировано
16
Scientific Reports, Год журнала: 2024, Номер 14(1)
Опубликована: Март 7, 2024
Abstract In this study, we aimed to develop a novel prognostic algorithm for oral squamous cell carcinoma (OSCC) using combination of pathogenomics and AI-based techniques. We collected comprehensive clinical, genomic, pathology data from cohort OSCC patients in the TCGA dataset used machine learning deep algorithms identify relevant features that are predictive survival outcomes. Our analyses included 406 patients. Initial involved gene expression analyses, principal component enrichment feature importance analyses. These insights were foundational subsequent model development. Furthermore, applied five learning/deep (Random Survival Forest, Gradient Boosting Analysis, Cox PH, Fast SVM, DeepSurv) prediction. initial revealed variations biological pathways, laying groundwork robust selection building. The results showed multimodal outperformed unimodal models across all methods, with c-index values 0.722 RSF, 0.633 GBSA, 0.625 FastSVM, CoxPH, 0.515 DeepSurv. When considering only important features, continued outperform models, 0.834 0.747 0.718 0.742 0.635 demonstrate potential techniques improving accuracy prediction OSCC, which may ultimately aid development personalized treatment strategies devastating disease.
Язык: Английский
Процитировано
14
Current Oncology, Год журнала: 2024, Номер 31(9), С. 5255 - 5290
Опубликована: Сен. 6, 2024
Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning natural language processing, their applications HNC. The integration of with imaging techniques, genomics, electronic health records explored, emphasizing its role early detection, biomarker discovery, planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, real-time monitoring systems are poised to further advance field. Addressing these fostering among experts, clinicians, researchers crucial developing equitable effective applications. future HNC holds significant promise, offering potential breakthroughs diagnostics, personalized therapies, improved patient outcomes.
Язык: Английский
Процитировано
9
International Dental Journal, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
To assess the knowledge, attitude, and practice of Dutch dentists on oral leukoplakia (OL) to what extent these aspects are related whether or not regularly monitor patients with OL.
Язык: Английский
Процитировано
1
Cancer Pathogenesis and Therapy, Год журнала: 2025, Номер unknown
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
1
Cureus, Год журнала: 2025, Номер unknown
Опубликована: Апрель 6, 2025
Oral squamous cell carcinoma (OSCC) is a serious worldwide health issue. Early OSCC identification by the analysis of digital oral photos possible with combination artificial intelligence (AI) and computer vision. The purpose this systematic review was to evaluate current evidence on role AI in diagnosis OSCC, focusing diagnostic performance, methodologies employed, potential limitations applications context. We followed Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA) guidelines search relevant studies across PubMed, Scopus, Web Science, Cumulative Index Nursing Allied Health Literature (CINAHL). In these databases, we found 286 studies, which were first screened duplicates then assessed inclusion exclusion criteria. Only 11 most included study. These also risk bias using Quality Assessment Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Numerous have shown impressive results job, frequently covering about 1000 regularly reaching sensitivity rates above 85% accuracy 90%. examines research detail, providing insight into their methods, include application contemporary machine learning pattern recognition techniques conjunction various supervision techniques. However, because datasets are utilized different articles, it can be difficult compare results. light results, study emphasizes how urgently area detection needs more solid trustworthy datasets. Additionally, sophisticated methods like ensemble learning, multi-task attention mechanisms used as essential instruments improve photos. Together, observations highlight AI-driven early greatly enhance patient outcomes medical procedures.
Язык: Английский
Процитировано
1
Oral Diseases, Год журнала: 2024, Номер unknown
Опубликована: Сен. 24, 2024
Abstract Objectives To update the current evidence on malignant transformation of oral leukoplakia (OL), including all studies published worldwide subject, selected with maximum rigor regarding eligibility. Materials and Methods MEDLINE, Embase, Web Science Scopus were searched for before June‐2024, no lower date limit. The risk bias was analyzed using Joanna Briggs Institute tool meta‐analyses proportions. We carried out meta‐analyses, explored heterogeneity across subgroups identified factors potential prognostic value. Results Fifty‐five (41,231 OL) included. pooled proportion OL 6.64% (95% CI = 5.21–8.21). did not significantly vary by time periods ( p 0.75), 5.35% prior to 1978, 7.06% from 1979 2007 6.97% during more recent times. that had a higher impact non‐homogeneous leukoplakias (RR 4.23, 95% 3.31–5.39, < 0.001), larger size 2.08, 1.45–2.96, located lateral border tongue (malignant 12.71%; RR 2.09, 1.48–2.95, smoking 1.64, 1.25–2.15, presence epithelial dysplasia 2.75, 2.26–3.35, 0.001). Conclusions presents considerable probability is especially increased in large lesions smokers, tongue, dysplasia.
Язык: Английский
Процитировано
8