Automated Detection of Oral Malignant Lesions Using Deep Learning: Scoping Review and Meta‐Analysis DOI Creative Commons
Olga Di Fede, Gaetano La Mantia, Marco Parola

et al.

Oral Diseases, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 3, 2024

ABSTRACT Objective Oral diseases, specifically malignant lesions, are serious global health concerns requiring early diagnosis for effective treatment. In recent years, deep learning (DL) has emerged as a powerful tool the automated detection and classification of oral lesions. This research, by conducting scoping review meta‐analysis, aims to provide an overview progress achievements in field lesions using DL. Materials Methods A was conducted identify relevant studies published last 5 years (2018–2023). comprehensive search several electronic databases, including PubMed, Web Science, Scopus. Two reviewers independently assessed eligibility extracted data standardized form, meta‐analysis synthesize findings. Results Fourteen utilizing various DL algorithms were identified included from clinical images. Among these, three meta‐analysis. The estimated pooled sensitivity specificity 0.86 (95% confidence interval [CI] = 0.80–0.91) 0.67 CI 0.58–0.75), respectively. Conclusions results indicate that improve Future research should develop validated diagnosis. Trial Registration Open Science Framework ( https://osf.io/4n8sm )

Language: Английский

Not Enough Dentistry DOI
Leila J. Mady, Wassim Najjar, Catherine Hayes

et al.

JAMA Otolaryngology–Head & Neck Surgery, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 23, 2025

This Viewpoint discusses the gap in dental insurance coverage for patients with head and neck cancer, many of whom forego care to treat or prevent oral complications cancer therapy due financial hardship.

Language: Английский

Citations

0
2024 ASCO guidelines for the prevention and management of osteoradionecrosis in patients with head & neck cancer treated with radiation therapy DOI
Douglas E. Peterson, Noam Yarom, Charlotte Duch Lynggaard

et al.

Current Opinion in Oncology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Purpose of review Osteoradionecrosis may often be prevented in context interprofessional healthcare that includes dental specialists prior to and following completion the patient's head neck radiation therapy. Important factors, however, compromise delivery guideline-concordant management osteoradionecrosis (ORN), including patient access this care. This is directed these related issues, order foster enhanced approaches for ORN management. Recent findings The centered 2024 Journal Clinical Oncology publication ‘Prevention Management Patients With Head Neck Cancer Treated Radiation Therapy: ISOO-MASCC-ASCO Guideline’, companion JCO Practice which clinical insights guideline are addressed. Key recent literature cited provide contemporary decision-making prevention early diagnosis treatment ORN. Although a relatively infrequent complication patients, can have profound financial impact when it occurs. Summary Interprofessional oncology care essential Future research needed enhance management, studies predicting risk development based on patient-centered factors.

Language: Английский

Citations

0
New trends in supportive care of head and neck cancers DOI

Ilaria Mascagni,

Paolo Bossi

Current Opinion in Oncology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Purpose of review Supportive care plays a vital role in the management head and neck cancer (HNC) patients, as disease often affects frail older population that is treated with multiple strategies associated severe symptoms. We will focus on mucositis, dermatitis, dysphagia, pain, cachexia, infections, they are among most common challenging symptoms encountered. Recent findings Efforts have focused multiomics approaches to decipher complex biological pathways drive symptom onset treatment-related toxicities, aim developing novel therapeutic strategies. A notable example ponsegromab, monoclonal antibody designed target cachexia. Other promising areas research, such machine-learning models oral gut microbiota cachexia actively being explored; however, their impact date remains limited. Summary In recent years, new knowledge has emerged regarding underlying causes predictive for supportive HNC patients. Unfortunately, this expanding body primarily adds complexity without translating into practical applications or substantial improvements Future efforts should prioritize standardization algorithms, generation robust evidence based existing preclinical models.

Language: Английский

Citations

0
Automated Detection of Oral Malignant Lesions Using Deep Learning: Scoping Review and Meta‐Analysis DOI Creative Commons
Olga Di Fede, Gaetano La Mantia, Marco Parola

et al.

Oral Diseases, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 3, 2024

ABSTRACT Objective Oral diseases, specifically malignant lesions, are serious global health concerns requiring early diagnosis for effective treatment. In recent years, deep learning (DL) has emerged as a powerful tool the automated detection and classification of oral lesions. This research, by conducting scoping review meta‐analysis, aims to provide an overview progress achievements in field lesions using DL. Materials Methods A was conducted identify relevant studies published last 5 years (2018–2023). comprehensive search several electronic databases, including PubMed, Web Science, Scopus. Two reviewers independently assessed eligibility extracted data standardized form, meta‐analysis synthesize findings. Results Fourteen utilizing various DL algorithms were identified included from clinical images. Among these, three meta‐analysis. The estimated pooled sensitivity specificity 0.86 (95% confidence interval [CI] = 0.80–0.91) 0.67 CI 0.58–0.75), respectively. Conclusions results indicate that improve Future research should develop validated diagnosis. Trial Registration Open Science Framework ( https://osf.io/4n8sm )

Language: Английский

Citations

2