ReviewFrontiers in genetics2021
Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature.
Review in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 31 citations in OpenAlex.
- Metabolomics-based analysis of the correlation between lipid metabolites and thyroid carcinoma.BMC biotechnology · 2025Article
- Development of a Machine Learning Model Integrating Pathomics and Clinical Data to Predict Axillary Lymph Node Metastasis in Breast Cancer: A Two-Center Study.Cancer reports (Hoboken, N.J.) · 2025Article
- Interpretable survival network for progression risk analysis of multimodality imaging biomarkers in poor-prognosis head and neck cancers.Scientific reports · 2024Article
- Review
- Epithelial‑derived head and neck squamous tumourigenesis (Review).Oncology reports · 2024Review
- Preliminary study on AI-assisted diagnosis of bone remodeling in chronic maxillary sinusitis.BMC medical imaging · 2024Article
- Applications and challenges of neural networks in otolaryngology (Review).Biomedical reports · 2024Review
- Recent advances in head and neck surgical oncology.Journal of surgical oncology · 2024Review
- Editorial of Special Issue "Oral Cancer: From Pathophysiology to Novel Therapeutic Approaches".Biomedicines · 2023Article
- Article
- Rise of Deep Learning Clinical Applications and Challenges in Omics Data: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging.PLOS digital health · 2023Article
- Combining Tumor Segmentation Masks with PET/CT Images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma.Head and neck tumor segmentation and outcome prediction : second challenge, HECKTOR 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings. Head and Neck Tumor Segmentation Challenge (2nd : 2021 ... · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Head and neck tumors are the sixth most common neoplasms. Multiomics integrates multiple dimensions of clinical, pathologic, radiological, and biological data and has the potential for tumor diagnosis and analysis. Deep learning (DL), a type of artificial intelligence (AI), is applied in medical image analysis. Among the DL techniques, the convolution neural network (CNN) is used for image segmentation, detection, and classification and in computer-aided diagnosis. Here, we reviewed multiomics image analysis of head and neck tumors using CNN and other DL neural networks. We also evaluated its application in early tumor detection, classification, prognosis/metastasis prediction, and the signing out of the reports. Finally, we highlighted the challenges and potential of these techniques.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.