ArticleScientific reports2022
Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 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
19 citing papers in PubMed, 50 citations in OpenAlex.
- Tongue Characteristics and Musculoskeletal Pain in Patients with Type 2 Diabetes Mellitus: A Principal Component and Latent Profile Analysis.Journal of pain research · 2026Article
- A dynamic weighted ensemble learning framework for cardiovascular risk prediction in type 2 diabetes: a comparative study with SHAP-based interpretability.Scientific reports · 2025Article
- Advanced deep feature engineering with crayfish optimization for diabetes detection using tongue images.Scientific reports · 2025Article
- Tongue shape classification based on IF-RCNet.Scientific reports · 2025Article
- Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study.BMC medical informatics and decision making · 2025Observational
- Emerging technologies for early risk stratification and precision management of diabetic kidney disease: a multimodal framework integrating digital phenotypes and clinical biomarkers.Frontiers in endocrinology · 2025Review
- Digital intelligence technology: new quality productivity for precision traditional Chinese medicine.Frontiers in pharmacology · 2025Review
- TongueNet: a multi-modal fusion and multi-label classification model for traditional Chinese Medicine tongue diagnosis.Frontiers in physiology · 2025Article
- Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.Scientific reports · 2024Article
- Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network.BMC medical imaging · 2024Article
- Integrating Artificial Intelligence in the Diagnosis of COPD Globally: A Way Forward.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2024Article
- Machine Learning as a Support for the Diagnosis of Type 2 Diabetes.International journal of molecular sciences · 2023Article
- The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review.Frontiers in public health · 2023Article
- Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review.Diabetology & metabolic syndrome · 2022Review
- Development and implementation of patient-level prediction models of end-stage renal disease for type 2 diabetes patients using fast healthcare interoperability resources.Scientific reports · 2022Article
- Deep Learning Multi-label Tongue Image Analysis and Its Application in a Population Undergoing Routine Medical Checkup.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Intelligent tongue and facial image analysis for noninvasive prediction of glucolipid metabolic disorders.Digital healthArticle
- Role of Artificial Intelligence in Diabetes Mellitus Care: A SWOT Analysis.Indian journal of endocrinology and metabolismReview
- A portable non-contact tongue imaging system with automated analysis for community and home settings.Digital healthArticle
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes is a serious metabolic disorder with high rate of prevalence worldwide; the disease has the characteristics of improper secretion of insulin in pancreas that results in high glucose level in blood. The disease is also associated with other complications such as cardiovascular disease, retinopathy, neuropathy and nephropathy. The development of computer aided decision support system is inevitable field of research for disease diagnosis that will assist clinicians for the early prognosis of diabetes and to facilitate necessary treatment at the earliest. In this research study, a Traditional Chinese Medicine based diabetes diagnosis is presented based on analyzing the extracted features of panoramic tongue images such as color, texture, shape, tooth markings and fur. The feature extraction is done by Convolutional Neural Network (CNN)-ResNet 50 architecture, and the classification is performed by the proposed Deep Radial Basis Function Neural Network (RBFNN) algorithm based on auto encoder learning mechanism. The proposed model is simulated in MATLAB environment and evaluated with performance metrics-accuracy, precision, sensitivity, specificity, F1 score, error rate, and receiver operating characteristics (ROC). On comparing with existing models, the proposed CNN based Deep RBFNN machine learning classifier model outperformed with better classification performance and proving its effectiveness.
Indexed as
Identifiers
What Socratic 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 Socratic graph.