On the public citation graph
An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival
0 signed · 137 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cncr.22963openalex-snapshot
Trends in head and neck cancer incidence in relation to smoking prevalence
inferredcites →https://doi.org/10.1002/cncr.28150openalex-snapshot
High intratumor genetic heterogeneity is related to worse outcome in patients with head and neck squamous cell carcinoma
inferredcites →https://doi.org/10.1002/hed.23553openalex-snapshot
Histologic and systemic prognosticators for local control and survival in margin‐negative transoral laser microsurgery treated oral cavity squamous cell carcinoma
inferredcites →https://doi.org/10.1002/hed.24507openalex-snapshot
Nomogram prediction for survival of patients with oral cavity squamous cell carcinoma
inferredcites →https://doi.org/10.1002/lary.24357openalex-snapshot
Grade as a prognostic factor in oral squamous cell carcinoma: A population‐based analysis of the data
inferredcites →https://doi.org/10.1007/978-3-642-40811-3_52openalex-snapshot
Spatially Aware Cell Cluster(SpACCl) Graphs: Predicting Outcome in Oropharyngeal p16+ Tumors
inferredcites →https://doi.org/10.1007/s11912-012-0216-1openalex-snapshot
Functional Outcomes after Chemoradiotherapy of Laryngeal and Pharyngeal Cancers
inferredcites →https://doi.org/10.1007/s12105-012-0412-1openalex-snapshot
Validation of the Risk Model: High-Risk Classification and Tumor Pattern of Invasion Predict Outcome for Patients with Low-Stage Oral Cavity Squamous Cell Carcinoma
inferredcites →https://doi.org/10.1016/j.media.2016.06.037openalex-snapshot
Image analysis and machine learning in digital pathology: Challenges and opportunities
inferredcites →https://doi.org/10.1016/j.oraloncology.2012.09.007openalex-snapshot
MATH, a novel measure of intratumor genetic heterogeneity, is high in poor-outcome classes of head and neck squamous cell carcinoma
inferredcites →https://doi.org/10.1016/s0140-6736(05)66544-0openalex-snapshot
Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials
inferredcites →https://doi.org/10.1038/modpathol.2015.68openalex-snapshot
Intratumoral morphologic and molecular heterogeneity of rhabdoid renal cell carcinoma: challenges for personalized therapy
inferredcites →https://doi.org/10.1038/ncomms12474openalex-snapshot
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
inferredcites →https://doi.org/10.1038/srep32706openalex-snapshot
Automated Tubule Nuclei Quantification and Correlation with Oncotype DX risk categories in ER+ Breast Cancer Whole Slide Images
inferredcites →https://doi.org/10.1056/nejmoa065497openalex-snapshot
Case–Control Study of Human Papillomavirus and Oropharyngeal Cancer
inferredcites →https://doi.org/10.1056/nejmoa1113205openalex-snapshot
Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
inferredcites →https://doi.org/10.1097/pas.0000000000000086openalex-snapshot
A Quantitative Histomorphometric Classifier (QuHbIC) Identifies Aggressive Versus Indolent p16-Positive Oropharyngeal Squamous Cell Carcinoma
inferredcites →https://doi.org/10.1097/pas.0000000000000256openalex-snapshot
High-grade Endometrial Stromal Sarcomas
inferredcites →https://doi.org/10.1097/pas.0b013e3181d95c37openalex-snapshot
Validation of the Histologic Risk Model in a New Cohort of Patients With Head and Neck Squamous Cell Carcinoma
inferredcites →https://doi.org/10.1109/isbi.2007.357094openalex-snapshot
AUTOMATED GRADING OF PROSTATE CANCER USING ARCHITECTURAL AND TEXTURAL IMAGE FEATURES
inferredcites →https://doi.org/10.1109/jbhi.2013.2277837openalex-snapshot
Toward Automatic Mitotic Cell Detection and Segmentation in Multispectral Histopathological Images
inferredcites →https://doi.org/10.1109/jbhi.2016.2544245openalex-snapshot
Automatic Nuclei Detection Based on Generalized Laplacian of Gaussian Filters
inferredcites →https://doi.org/10.1109/tbme.2013.2245129openalex-snapshot
Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast Cancer From Entire Histopathology Slides
inferredcites →https://doi.org/10.1109/tpami.2005.159openalex-snapshot
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
inferredcites →https://doi.org/10.1111/j.1365-2559.2010.03616.xopenalex-snapshot
Invasive pattern grading score designed as an independent prognostic indicator in oral squamous cell carcinoma
inferredcites →https://doi.org/10.1126/scitranslmed.3002564openalex-snapshot
Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival
inferredcites →https://doi.org/10.1146/annurev-bioeng-112415-114722openalex-snapshot
Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology
inferredcites →https://doi.org/10.1155/2014/247853openalex-snapshot
Prognostic Efficacy of Nuclear Morphometry at Invasive Front of Oral Squamous Cell Carcinoma: An Image Analysis Microscopic Study
inferredcites →https://doi.org/10.1159/000446117openalex-snapshot
Global Epidemiology of Head and Neck Cancers: A Continuing Challenge
inferredcites →https://doi.org/10.1177/0194599816636356openalex-snapshot
Impact of Nodal Level Distribution on Survival in Oral Cavity Squamous Cell Carcinoma
inferredcites →https://doi.org/10.1186/s12885-015-1380-0openalex-snapshot
Fractal analysis of nuclear histology integrates tumor and stromal features into a single prognostic factor of the oral cancer microenvironment
inferredcites →https://doi.org/10.1200/jco.2013.50.3870openalex-snapshot
Worldwide Trends in Incidence Rates for Oral Cavity and Oropharyngeal Cancers
inferredcites →https://doi.org/10.1371/journal.pmed.1001786openalex-snapshot
Intra-tumor Genetic Heterogeneity and Mortality in Head and Neck Cancer: Analysis of Data from The Cancer Genome Atlas
inferredcites →https://doi.org/10.1371/journal.pone.0070221openalex-snapshot
Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images
inferredcites →https://doi.org/10.1371/journal.pone.0104979openalex-snapshot
Reporting Tumor Molecular Heterogeneity in Histopathological Diagnosis
inferredcites →https://doi.org/10.1593/neo.131400openalex-snapshot
Tumor Evolution and Intratumor Heterogeneity of an Oropharyngeal Squamous Cell Carcinoma Revealed by Whole-Genome Sequencing
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/0471266949.bmc301openalex-snapshot
Docking, Scoring, and Virtual Screening in Drug Discovery
inferred← citeshttps://doi.org/10.1002/cjp2.344openalex-snapshot
Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features
inferred← citeshttps://doi.org/10.1002/cncr.34446openalex-snapshot
Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus‐associated oropharyngeal squamous cell carcinoma
inferred← citeshttps://doi.org/10.1002/ima.70017openalex-snapshot
DBE ‐Net: A Dual‐Branch Boundary Enhancement Network for Pathological Image Segmentation
inferred← citeshttps://doi.org/10.1002/inmd.20240037openalex-snapshot
Application of quantitative histomorphometric features in computational pathology
inferred← citeshttps://doi.org/10.1002/jcb.29615openalex-snapshot
The exploration of new therapeutic targets for HPV‐negative head and neck squamous cell cancer through the construction of a ceRNA network and immune microenvironment analysis
inferred← citeshttps://doi.org/10.1002/lary.30351openalex-snapshot
Novel Machine Learning Model to Predict Interval of Oral Cancer Recurrence for Surveillance Stratification
inferred← citeshttps://doi.org/10.1002/med.21847openalex-snapshot
Association predictions of genomics, proteinomics, transcriptomics, microbiome, metabolomics, pathomics, radiomics, drug, symptoms, environment factor, and disease networks: A comprehensive approach
inferred← citeshttps://doi.org/10.1002/path.5864openalex-snapshot
Computer‐extracted features of nuclear morphology in hematoxylin and eosin images distinguish s tage II and IV colon tumors
inferred← citeshttps://doi.org/10.1002/widm.1410openalex-snapshot
A 2021 update on cancer image analytics with deep learning
inferred← citeshttps://doi.org/10.1007/978-3-030-69859-1_6openalex-snapshot
Deep Learning-Based Cancer Region Segmentation from H&E Slides for HPV-Related Oropharyngeal Squamous Cell Carcinomas
inferred← citeshttps://doi.org/10.1007/978-3-031-17266-3_1openalex-snapshot
Cellular Architecture on Whole Slide Images Allows the Prediction of Survival in Lung Adenocarcinoma
inferred← citeshttps://doi.org/10.1007/978-3-031-87873-2_6openalex-snapshot
Colon Cancer Survival Prediction from Epithelium Nuclei Morphological Features Within Histology Slides Using Deep Learning
inferred← citeshttps://doi.org/10.1007/s10006-025-01334-6openalex-snapshot
The current landscape of artificial intelligence in oral and maxillofacial surgery– a narrative review
inferred← citeshttps://doi.org/10.1007/s10462-021-10058-4openalex-snapshot
Machine Learning in Drug Discovery: A Review
inferred← citeshttps://doi.org/10.1007/s11831-025-10275-yopenalex-snapshot
A comprehensive review on step-based skin cancer detection using machine learning and deep learning methods
inferred← citeshttps://doi.org/10.1007/s12070-024-05008-9openalex-snapshot
Histomorphometric Analysis of Oral Squamous Cell Carcinoma, Apparently Normal Adjacent Mucosa and Epithelial Dysplasia
inferred← citeshttps://doi.org/10.1016/b978-0-443-27523-4.00009-3openalex-snapshot
Deep learning for network building and analysis of biological networks: A case study
inferred← citeshttps://doi.org/10.1016/b978-0-443-45004-4.00011-6openalex-snapshot
AI in designing novel cancer treatments
inferred← citeshttps://doi.org/10.1016/j.artmed.2021.102060openalex-snapshot
Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future—A systematic review
inferred← citeshttps://doi.org/10.1016/j.bbiosy.2021.100012openalex-snapshot
The convergence of high-tech emerging technologies into the next stage of organ-on-a-chips
inferred← citeshttps://doi.org/10.1016/j.canlet.2019.12.007openalex-snapshot
Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges
inferred← citeshttps://doi.org/10.1016/j.canlet.2025.218134openalex-snapshot
A deep learning framework to iDentify prOgnostically releVant cancEr Regions (DOVER) within whole slide histopathology images
inferred← citeshttps://doi.org/10.1016/j.canrad.2021.06.027openalex-snapshot
Intelligence artificielle en radiothérapie : radiomique, pathomique, et prédiction de la survie et de la réponse aux traitements
inferred← citeshttps://doi.org/10.1016/j.cden.2025.11.009openalex-snapshot
Artificial Intelligence and Its Applications in Oral and Maxillofacial Pathology
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.105209openalex-snapshot
AI-based carcinoma detection and classification using histopathological images: A systematic review
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.105520openalex-snapshot
Survival prediction on intrahepatic cholangiocarcinoma with histomorphological analysis on the whole slide images
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106228openalex-snapshot
Automatic multi-tissue segmentation in pancreatic pathological images with selected multi-scale attention network
inferred← citeshttps://doi.org/10.1016/j.esmoop.2025.105757openalex-snapshot
Artificial intelligence defines spatial patterns of tumor-infiltrating lymphocytes highly associated with outcome – a pan-GI cancer study
inferred← citeshttps://doi.org/10.1016/j.identj.2025.02.005openalex-snapshot
The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview. Part 1: Fundamentals of AI, and its Contemporary Applications in Dentistry
inferred← citeshttps://doi.org/10.1016/j.ijmedinf.2020.104313openalex-snapshot
Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer
inferred← citeshttps://doi.org/10.1016/j.ijmedinf.2021.104557openalex-snapshot
Prediction models applying machine learning to oral cavity cancer outcomes: A systematic review
inferred← citeshttps://doi.org/10.1016/j.iswa.2026.200736openalex-snapshot
An update of artificial intelligence in pathology: Current applications, challenges, and future directions
inferred← citeshttps://doi.org/10.1016/j.jdent.2025.105648openalex-snapshot
Artificial intelligence in dentistry: Exploring emerging applications and future prospects
inferred← citeshttps://doi.org/10.1016/j.oor.2024.100591openalex-snapshot
Harnessing artificial intelligence for predictive modelling in oral oncology: Opportunities, challenges, and clinical Perspectives
inferred← citeshttps://doi.org/10.1016/j.oraloncology.2021.105254openalex-snapshot
The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer
inferred← citeshttps://doi.org/10.1016/j.oraloncology.2022.105942openalex-snapshot
A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study
inferred← citeshttps://doi.org/10.1016/j.oraloncology.2025.107742openalex-snapshot
Integrating artificial intelligence-driven digital pathology and genomics to establish patient-derived organoids as new approach methodologies for drug response in head and neck cancer
inferred← citeshttps://doi.org/10.1016/j.semcancer.2023.07.002openalex-snapshot
Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives
inferred← citeshttps://doi.org/10.1016/j.tibtech.2018.08.005openalex-snapshot
Deep Learning with Microfluidics for Biotechnology
inferred← citeshttps://doi.org/10.1038/s41374-018-0095-7openalex-snapshot
Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers
inferred← citeshttps://doi.org/10.1038/s41416-021-01386-xopenalex-snapshot
Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview
inferred← citeshttps://doi.org/10.1038/s41523-025-00860-6openalex-snapshot
Prognostic value of nuclear features based on tumor-associated collagen signatures in breast cancer
inferred← citeshttps://doi.org/10.1038/s41571-019-0252-yopenalex-snapshot
Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
inferred← citeshttps://doi.org/10.1038/s41573-019-0024-5openalex-snapshot
Applications of machine learning in drug discovery and development
inferred← citeshttps://doi.org/10.1038/s41598-019-49710-zopenalex-snapshot
A Novel Digital Score for Abundance of Tumour Infiltrating Lymphocytes Predicts Disease Free Survival in Oral Squamous Cell Carcinoma
inferred← citeshttps://doi.org/10.1038/s41698-024-00775-8openalex-snapshot
Extreme wrinkling of the nuclear lamina is a morphological marker of cancer
inferred← citeshttps://doi.org/10.1038/s41746-025-02014-1openalex-snapshot
AI-driven prediction of progression to oral squamous cell carcinoma using a multiresolution pathology model
inferred← citeshttps://doi.org/10.1049/cit2.12175openalex-snapshot
Predicting recurrence in osteosarcoma via a quantitative histological image classifier derived from tumour nuclear morphological features
inferred← citeshttps://doi.org/10.1051/mbcb/2023018openalex-snapshot
Knowledge, attitude, and perception of dentists regarding the role of Artificial Intelligence and its applications in Oral Medicine and Radiology: a cross sectional study
inferred← citeshttps://doi.org/10.1093/bioinformatics/btac677openalex-snapshot
A novel pipeline for computerized mouse spermatogenesis staging
inferred← citeshttps://doi.org/10.1097/cco.0000000000000731openalex-snapshot
Perspectives in pathomics in head and neck cancer
inferred← citeshttps://doi.org/10.1101/2025.06.24.660824openalex-snapshot
Integrating Artificial Intelligence-Driven Digital Pathology and Genomics to Establish Patient-Derived Organoids as a Novel Alternative Model for Drug Response in Head and Neck Cancer
inferred← citeshttps://doi.org/10.1109/3ict56508.2022.9990784openalex-snapshot
Cancer Diagnosis based on Artificial Intelligence, Machine Learning, and Deep Learning
inferred← citeshttps://doi.org/10.1111/jop.13042openalex-snapshot
The use of artificial intelligence, machine learning and deep learning in oncologic histopathology
inferred← citeshttps://doi.org/10.1111/jop.70002openalex-snapshot
Exploring the Role of Artificial Intelligence in Oral Pathology: Diagnostic and Prognostic Implications
inferred← citeshttps://doi.org/10.1117/1.jmi.8.s1.017501openalex-snapshot
Computational pathology reveals unique spatial patterns of immune response in H&E images from COVID-19 autopsies: preliminary findings
inferred← citeshttps://doi.org/10.1117/12.2613387openalex-snapshot
Identifying the origination of liver metastasis using a hand-crafted computational pathology approach
inferred← citeshttps://doi.org/10.1117/12.3005006openalex-snapshot
Robust tissue differentiation in head and neck cancer: ex-vivo study with hyperspectral imaging and convolutional neural networks
inferred← citeshttps://doi.org/10.1136/jcp-2026-210720openalex-snapshot
Promise and pragmatism of AI in global-scale digital pathology: pan-cancer approaches for clinical practice
inferred← citeshttps://doi.org/10.1161/circulationaha.121.058459openalex-snapshot
Computational Analysis of Routine Biopsies Improves Diagnosis and Prediction of Cardiac Allograft Vasculopathy
inferred← citeshttps://doi.org/10.1172/jci145488openalex-snapshot
Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma
inferred← citeshttps://doi.org/10.1186/s12885-024-11954-yopenalex-snapshot
The prognostic role of single cell invasion and nuclear diameter in early oral tongue squamous cell carcinoma
inferred← citeshttps://doi.org/10.1186/s12903-022-02336-6openalex-snapshot
Correlation of histopathological patterns of OSCC patients with tumor site and habits
inferred← citeshttps://doi.org/10.1186/s12903-026-07658-3openalex-snapshot
Application of artificial intelligence and radiomics in the prediction of lymph node metastasis and tumour grading of oral cancer - a systematic review and meta analysis
inferred← citeshttps://doi.org/10.1186/s12967-019-1839-xopenalex-snapshot
Nuclear shape, architecture and orientation features from H&E images are able to predict recurrence in node-negative gastric adenocarcinoma
inferred← citeshttps://doi.org/10.1186/s12967-020-02297-wopenalex-snapshot
Glandular orientation and shape determined by computational pathology could identify aggressive tumor for early colon carcinoma: a triple-center study
inferred← citeshttps://doi.org/10.1186/s13058-019-1200-6openalex-snapshot
Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings
inferred← citeshttps://doi.org/10.1186/s40537-023-00703-wopenalex-snapshot
Data-centric artificial intelligence in oncology: a systematic review assessing data quality in machine learning models for head and neck cancer
inferred← citeshttps://doi.org/10.1186/s40779-025-00680-6openalex-snapshot
Artificial intelligence in digital pathology diagnosis and analysis: technologies, challenges, and future prospects
inferred← citeshttps://doi.org/10.1200/cci.20.00110openalex-snapshot
Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology
inferred← citeshttps://doi.org/10.14393/ufu.di.2020.710openalex-snapshot
Uso da inteligência artificial na caracterização nuclear e classificação entre leucoplasia bucal e leucoplasia verrucosa proliferativa
inferred← citeshttps://doi.org/10.17721/fujcv13i1p1-66openalex-snapshot
Machine Learning Applications in Drug Discovery
inferred← citeshttps://doi.org/10.21053/ceo.2020.00654openalex-snapshot
Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery
inferred← citeshttps://doi.org/10.31917/2304234openalex-snapshot
OPPORTUNITIES AND PROSPECTS OF ARTIFICIAL INTELLIGENCE IN THE PATHOLOGICAL IDENTIFICATION OF CANCER
inferred← citeshttps://doi.org/10.3238/arztebl.m2021.0011openalex-snapshot
Artificial Intelligence in Pathology
inferred← citeshttps://doi.org/10.33448/rsd-v10i5.13319openalex-snapshot
Diagnóstico precoce do câncer bucal com inteligência artificial: Uma revisão integrativa
inferred← citeshttps://doi.org/10.33854/jbd.v10i2.1460openalex-snapshot
SALIVARY IL-6 AND IL-8 AS POTENTIAL BIOMARKERS FOR ORAL SQUAMOUS CELL CARCINOMA
inferred← citeshttps://doi.org/10.3389/fgene.2021.624820openalex-snapshot
Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature
inferred← citeshttps://doi.org/10.3390/app12115715openalex-snapshot
Machine-Learning Applications in Oral Cancer: A Systematic Review
inferred← citeshttps://doi.org/10.3390/biomedicines11061612openalex-snapshot
Application and Performance of Artificial Intelligence (AI) in Oral Cancer Diagnosis and Prediction Using Histopathological Images: A Systematic Review
inferred← citeshttps://doi.org/10.3390/cancers15194824openalex-snapshot
Automated Cellular-Level Dual Global Fusion of Whole-Slide Imaging for Lung Adenocarcinoma Prognosis
inferred← citeshttps://doi.org/10.3390/cancers18111818openalex-snapshot
Clinical Implications of Polyploid Giant Cancer Cells in Solid Tumors: Biology, Diagnosis, and Therapeutic Considerations
inferred← citeshttps://doi.org/10.3390/cimb46010018openalex-snapshot
Recent Advances in Liver Tissue Engineering as an Alternative and Complementary Approach for Liver Transplantation
inferred← citeshttps://doi.org/10.3390/jcm10225326openalex-snapshot
Deep Learning on Oral Squamous Cell Carcinoma Ex Vivo Fluorescent Confocal Microscopy Data: A Feasibility Study
inferred← citeshttps://doi.org/10.3390/medicina58081059openalex-snapshot
A Survey on the Use of Artificial Intelligence by Clinicians in Dentistry and Oral and Maxillofacial Surgery
inferred← citeshttps://doi.org/10.34248/bsengineering.1528581openalex-snapshot
Oral Cancer Classification with CNN Based State-of-the-art Transfer Learning Methods
inferred← citeshttps://doi.org/10.3892/ijo.2023.5555openalex-snapshot
Artificial intelligence in cancer pathology: Challenge to meet increasing demands of precision medicine
inferred← citeshttps://doi.org/10.4103/jomfp.jomfp_41_25openalex-snapshot
Deoxyelephantopin induces cell death in oral cancer cells via the downregulation of AKT1-mTOR-mediated mechanisms
inferred← citeshttps://doi.org/10.47749/t/unicamp.2022.1257145openalex-snapshot
Machine Learning aplicada às investigações nos campos da Estomatologia e da Patologia Oral e Maxilofacial
inferred← citeshttps://doi.org/10.51847/aqajto9n1uopenalex-snapshot
Artificial Intelligence in Oral Pathology Practice– An Overview
inferred← citeshttps://doi.org/10.5772/dmht.20openalex-snapshot
Application of Artificial Intelligence in Different Fields of Oromaxillofacial Surgery
inferred← citeshttps://doi.org/10.6084/m9.figshare.11992386openalex-snapshot
Additional file 1 of Glandular orientation and shape determined by computational pathology could identify aggressive tumor for early colon carcinoma: a triple-center study
inferred← citeshttps://doi.org/10.70675/7f14ed99zef37z40dfz90c8z771964ff8a4aopenalex-snapshot
Dendritic Cells in Head and Neck Cancer Microenvironment : From Mechanisms to Biomarkers
inferred← citeshttps://doi.org/10.70675/8d10f89dz0f91z4e9dzb3a8zb5228b1172c1openalex-snapshot
Weakly Supervised Segmentation and Context-Aware Classification in Computational Pathology
inferred← citeshttps://doi.org/10.70675/b672dc67zccbcz48ffz84a1z2c224407c9a1openalex-snapshot
Nouvelles approches de machine learning pour l'analyse de données en pathologie numérique : application aux lymphomes primitifs du système nerveux central et extension à d'autres pathologies tumorales
inferred← citeshttps://doi.org/10.7759/cureus.53458openalex-snapshot
Hesperidin Inhibits Oral Cancer Cell Growth via Apoptosis and Inflammatory Signaling-Mediated Mechanisms: Evidence From In Vitro and In Silico Analyses
inferred← citeshttps://doi.org/10.9734/jammr/2023/v35i105018openalex-snapshot
The Role of Cell Detection Tool of QuPath-0.3.2 Software in Differentiating Benign Cervical Epithelium from Malignant Epithelial Clusters
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.