On the public citation graph
A 2021 update on cancer image analytics with deep learning
0 signed · 197 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known work and none has been retracted — and get a dated CiteStamped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/10.1001/jama.2017.14585openalex-snapshot
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
inferredcites →https://doi.org/10.1001/jamaoncol.2020.2485openalex-snapshot
Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens
inferredcites →https://doi.org/10.1002/ana.25839openalex-snapshot
Optic Disc Classification by Deep Learning versus Expert Neuro‐Ophthalmologists
inferredcites →https://doi.org/10.1002/cam4.2233openalex-snapshot
Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning
inferredcites →https://doi.org/10.1002/cncr.28493openalex-snapshot
Intraobserver and interobserver variability in computed tomography size and attenuation measurements in patients with renal cell carcinoma receiving antiangiogenic therapy: Implications for alternative response criteria
inferredcites →https://doi.org/10.1002/cyto.a.23065openalex-snapshot
A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers
inferredcites →https://doi.org/10.1002/mrm.22147openalex-snapshot
Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme
inferredcites →https://doi.org/10.1007/978-3-030-00889-5_1openalex-snapshot
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-11726-9_32openalex-snapshot
S3D-UNet: Separable 3D U-Net for Brain Tumor Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-11726-9_33openalex-snapshot
Deep Learning Radiomics Algorithm for Gliomas (DRAG) Model: A Novel Approach Using 3D UNET Based Deep Convolutional Neural Network for Predicting Survival in Gliomas
inferredcites →https://doi.org/10.1007/978-3-030-17798-0_32openalex-snapshot
Automatic Nucleus Segmentation with Mask-RCNN
inferredcites →https://doi.org/10.1007/978-3-030-23937-4_2openalex-snapshot
PanNuke: An Open Pan-Cancer Histology Dataset for Nuclei Instance Segmentation and Classification
inferredcites →https://doi.org/10.1007/978-3-030-32239-7_55openalex-snapshot
Deep Multi-instance Learning for Survival Prediction from Whole Slide Images
inferredcites →https://doi.org/10.1007/978-3-030-32239-7_57openalex-snapshot
Deep Instance-Level Hard Negative Mining Model for Histopathology Images
inferredcites →https://doi.org/10.1007/978-3-030-59719-1_56openalex-snapshot
One Click Lesion RECIST Measurement and Segmentation on CT Scans
inferredcites →https://doi.org/10.1007/978-3-319-10578-9_23openalex-snapshot
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot
SSD: Single Shot MultiBox Detector
inferredcites →https://doi.org/10.1007/978-3-319-46466-4_5openalex-snapshot
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles
inferredcites →https://doi.org/10.1007/978-981-15-7981-3_21openalex-snapshot
Complex-Valued Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1007/978-981-16-8048-9openalex-snapshot
Advances in Intelligent Systems and Computing
inferredcites →https://doi.org/10.1007/bf02478259openalex-snapshot
A logical calculus of the ideas immanent in nervous activity
inferredcites →https://doi.org/10.1007/s10278-011-9366-1openalex-snapshot
Five Levels of PACS Modularity: Integrating 3D and Other Advanced Visualization Tools
inferredcites →https://doi.org/10.1007/s10278-016-9873-1openalex-snapshot
Localization of Diagnostically Relevant Regions of Interest in Whole Slide Images: a Comparative Study
inferredcites →https://doi.org/10.1007/s10278-018-0082-yopenalex-snapshot
The Orthanc Ecosystem for Medical Imaging
inferredcites →https://doi.org/10.1007/s11042-020-10010-8openalex-snapshot
AI aiding in diagnosing, tracking recovery of COVID-19 using deep learning on Chest CT scans
inferredcites →https://doi.org/10.1007/s11517-020-02175-zopenalex-snapshot
MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images
inferredcites →https://doi.org/10.1007/s11548-019-01948-8openalex-snapshot
Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in CT data for lung cancer staging
inferredcites →https://doi.org/10.1016/j.addr.2015.03.009openalex-snapshot
Raman spectroscopy for medical diagnostics — From in-vitro biofluid assays to in-vivo cancer detection
inferredcites →https://doi.org/10.1016/j.annonc.2020.04.477openalex-snapshot
Deep learning as a staging tool in gastric cancer
inferredcites →https://doi.org/10.1016/j.artint.2013.06.003openalex-snapshot
Multiple instance classification: Review, taxonomy and comparative study
inferredcites →https://doi.org/10.1016/j.clbc.2018.04.019openalex-snapshot
Hot Spot and Whole-Tumor Enumeration of CD8+ Tumor-Infiltrating Lymphocytes Utilizing Digital Image Analysis Is Prognostic in Triple-Negative Breast Cancer
inferredcites →https://doi.org/10.1016/j.cmpb.2018.01.017openalex-snapshot
Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system
inferredcites →https://doi.org/10.1016/j.compmedimag.2017.12.001openalex-snapshot
Efficient deep learning model for mitosis detection using breast histopathology images
inferredcites →https://doi.org/10.1016/j.ejca.2016.03.081openalex-snapshot
RECIST 1.1—Update and clarification: From the RECIST committee
inferredcites →https://doi.org/10.1016/j.ejca.2019.06.012openalex-snapshot
Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images
inferredcites →https://doi.org/10.1016/j.ejrad.2019.01.028openalex-snapshot
Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases
inferredcites →https://doi.org/10.1016/j.eswa.2018.09.049openalex-snapshot
Multiple instance learning for histopathological breast cancer image classification
inferredcites →https://doi.org/10.1016/j.eururo.2014.10.036openalex-snapshot
A Genomic Classifier Improves Prediction of Metastatic Disease Within 5 Years After Surgery in Node-negative High-risk Prostate Cancer Patients Managed by Radical Prostatectomy Without Adjuvant Therapy
inferredcites →https://doi.org/10.1016/j.media.2019.101563openalex-snapshot
Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
inferredcites →https://doi.org/10.1016/j.media.2019.101624openalex-snapshot
Graph temporal ensembling based semi-supervised convolutional neural network with noisy labels for histopathology image analysis
inferredcites →https://doi.org/10.1016/j.neucom.2018.07.079openalex-snapshot
AlphaMEX: A smarter global pooling method for convolutional neural networks
inferredcites →https://doi.org/10.1016/s1361-3723(16)30028-8openalex-snapshot
A new era in data protection
inferredcites →https://doi.org/10.1016/s1470-2045(19)30739-9openalex-snapshot
Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study
inferredcites →https://doi.org/10.1016/s2589-7500(19)30123-2openalex-snapshot
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
inferredcites →https://doi.org/10.1016/s2589-7500(20)30078-9openalex-snapshot
Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation
inferredcites →https://doi.org/10.1017/9781139061773.019openalex-snapshot
Transfer Learning in Computer Vision
inferredcites →https://doi.org/10.1038/323533a0openalex-snapshot
Learning representations by back-propagating errors
inferredcites →https://doi.org/10.1038/modpathol.2017.98openalex-snapshot
An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival
inferredcites →https://doi.org/10.1038/s41374-019-0275-0openalex-snapshot
Deep learning assisted mitotic counting for breast cancer
inferredcites →https://doi.org/10.1038/s41467-020-19116-xopenalex-snapshot
Non-invasive decision support for NSCLC treatment using PET/CT radiomics
inferredcites →https://doi.org/10.1038/s41523-018-0079-1openalex-snapshot
Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype
inferredcites →https://doi.org/10.1038/s41551-020-00682-wopenalex-snapshot
Data-efficient and weakly supervised computational pathology on whole-slide images
inferredcites →https://doi.org/10.1038/s41591-018-0177-5openalex-snapshot
Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
inferredcites →https://doi.org/10.1038/s41591-019-0447-xopenalex-snapshot
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
inferredcites →https://doi.org/10.1038/s41598-017-05728-9openalex-snapshot
Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR
inferredcites →https://doi.org/10.1038/s41598-018-35501-5openalex-snapshot
Deep Semi Supervised Generative Learning for Automated Tumor Proportion Scoring on NSCLC Tissue Needle Biopsies
inferredcites →https://doi.org/10.1038/s41598-019-40041-7openalex-snapshot
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
inferredcites →https://doi.org/10.1038/s41598-019-42557-4openalex-snapshot
Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization
inferredcites →https://doi.org/10.1038/s41598-019-48738-5openalex-snapshot
Image-based Classification of Tumor Type and Growth Rate using Machine Learning: a preclinical study
inferredcites →https://doi.org/10.1038/s41598-019-48995-4openalex-snapshot
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
inferredcites →https://doi.org/10.1038/s41598-020-58467-9openalex-snapshot
Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours
inferredcites →https://doi.org/10.1038/s41598-020-60311-zopenalex-snapshot
Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone
inferredcites →https://doi.org/10.1038/s41598-020-69250-1openalex-snapshot
Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
inferredcites →https://doi.org/10.1038/sdata.2017.177openalex-snapshot
A curated mammography data set for use in computer-aided detection and diagnosis research
inferredcites →https://doi.org/10.1073/pnas.1821594116openalex-snapshot
What are the limits of deep learning?
inferredcites →https://doi.org/10.1080/21681163.2016.1141063openalex-snapshot
A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images
inferredcites →https://doi.org/10.1088/1361-6560/aaa1caopenalex-snapshot
Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm
inferredcites →https://doi.org/10.1088/1361-6560/ab8cd6openalex-snapshot
Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy
inferredcites →https://doi.org/10.1093/annonc/mdz413.116openalex-snapshot
A Bayesian framework to quantify survival uncertainty
inferredcites →https://doi.org/10.1093/bioinformatics/btz342openalex-snapshot
Deep learning with multimodal representation for pancancer prognosis prediction
inferredcites →https://doi.org/10.1093/gigascience/giy065openalex-snapshot
1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
inferredcites →https://doi.org/10.1093/jamia/ocv180openalex-snapshot
Extracting information from the text of electronic medical records to improve case detection: a systematic review
inferredcites →https://doi.org/10.1093/jamia/ocx132openalex-snapshot
CLAMP – a toolkit for efficiently building customized clinical natural language processing pipelines
inferredcites →https://doi.org/10.1093/jamia/ocy017openalex-snapshot
Distributed deep learning networks among institutions for medical imaging
inferredcites →https://doi.org/10.1093/noajnl/vdaa110openalex-snapshot
Optimization of deep learning methods for visualization of tumor heterogeneity and brain tumor grading through digital pathology
inferredcites →https://doi.org/10.1097/01.ju.0000158155.33890.e7openalex-snapshot
The University of California, San Francisco Cancer of the Prostate Risk Assessment Score
inferredcites →https://doi.org/10.1097/jto.0b013e31826aec2bopenalex-snapshot
Overall Survival Improvement in Patients with Lung Cancer and Bone Metastases Treated with Denosumab Versus Zoledronic Acid: Subgroup Analysis from a Randomized Phase 3 Study
inferredcites →https://doi.org/10.1097/md.0000000000003770openalex-snapshot
Identification of High-Risk Subgroups of Patients With Oral Cavity Cancer in Need of Postoperative Adjuvant Radiotherapy or Chemo-Radiotherapy
inferredcites →https://doi.org/10.1097/pas.0000000000001151openalex-snapshot
Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer
inferredcites →https://doi.org/10.1098/rsif.2017.0387openalex-snapshot
Opportunities and obstacles for deep learning in biology and medicine
inferredcites →https://doi.org/10.1101/554261openalex-snapshot
Gaussian Process Based Heteroscedastic Noise Modeling for Tumor Mutation Burden Prediction from Whole Slide Images
inferredcites →https://doi.org/10.1109/cbms49503.2020.00111openalex-snapshot
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/compsac48688.2020.00-84openalex-snapshot
Deep Learning for Visual Segmentation: A Review
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2016.278openalex-snapshot
Context Encoders: Feature Learning by Inpainting
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.96openalex-snapshot
Colorization as a Proxy Task for Visual Understanding
inferredcites →https://doi.org/10.1109/cvpr.2019.00873openalex-snapshot
Robust Histopathology Image Analysis: To Label or to Synthesize?
inferredcites →https://doi.org/10.1109/icassp.2019.8682496openalex-snapshot
A Deep Dual-path Network for Improved Mammogram Image Processing
inferredcites →https://doi.org/10.1109/icip.2016.7532839openalex-snapshot
Detecting multiple sub-types of breast cancer in a single patient
inferredcites →https://doi.org/10.1109/icpr.2016.7900002openalex-snapshot
Deep learning for magnification independent breast cancer histopathology image classification
inferredcites →https://doi.org/10.1109/isbi.2018.8363576openalex-snapshot
Synthetic data augmentation using GAN for improved liver lesion classification
inferredcites →https://doi.org/10.1109/isbi.2018.8363642openalex-snapshot
Multiple instance learning of deep convolutional neural networks for breast histopathology whole slide classification
inferredcites →https://doi.org/10.1109/isbi.2019.8759182openalex-snapshot
Few Shot Learning in Histopathological Images:Reducing the Need of Labeled Data on Biological Datasets
inferredcites →https://doi.org/10.1109/isbi.2019.8759203openalex-snapshot
Robust Learning at Noisy Labeled Medical Images: Applied to Skin Lesion Classification
inferredcites →https://doi.org/10.1109/isbi.2019.8759574openalex-snapshot
Mask-RCNN and U-Net Ensembled for Nuclei Segmentation
inferredcites →https://doi.org/10.1109/nssmic.2018.8824538openalex-snapshot
Development of deep learning model for prediction of chemotherapy response using PET images and radiomics features
inferredcites →https://doi.org/10.1109/tmi.2016.2525803openalex-snapshot
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
inferredcites →https://doi.org/10.1109/tmi.2016.2528120openalex-snapshot
AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images
inferredcites →https://doi.org/10.1109/tmi.2017.2677499openalex-snapshot
A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology
inferredcites →https://doi.org/10.1109/tmi.2017.2724070openalex-snapshot
Constrained Deep Weak Supervision for Histopathology Image Segmentation
inferredcites →https://doi.org/10.1109/tmi.2018.2845918openalex-snapshot
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes
inferredcites →https://doi.org/10.1109/tmi.2018.2867350openalex-snapshot
From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge
inferredcites →https://doi.org/10.1109/tmi.2019.2947628openalex-snapshot
A Multi-Organ Nucleus Segmentation Challenge
inferredcites →https://doi.org/10.1109/tmi.2021.3056023openalex-snapshot
Self-Path: Self-Supervision for Classification of Pathology Images With Limited Annotations
inferredcites →https://doi.org/10.1109/tpami.2016.2572683openalex-snapshot
Fully Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2016.2644615openalex-snapshot
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
inferredcites →https://doi.org/10.1111/his.13528openalex-snapshot
Digital image analysis improves precision of PD ‐L1 scoring in cutaneous melanoma
inferredcites →https://doi.org/10.1117/1.jmi.7.1.016502openalex-snapshot
Integrating AI into radiology workflow: levels of research, production, and feedback maturity
inferredcites →https://doi.org/10.1117/12.2255774openalex-snapshot
Convolutional neural networks for prostate cancer recurrence prediction
inferredcites →https://doi.org/10.1117/12.2293699openalex-snapshot
Using YOLO based deep learning network for real time detection and localization of lung nodules from low dose CT scans
inferredcites →https://doi.org/10.1118/1.4944498openalex-snapshot
Urinary bladder segmentation in CT urography using deep‐learning convolutional neural network and level sets
inferredcites →https://doi.org/10.1136/medethics-2019-105586openalex-snapshot
On the ethics of algorithmic decision-making in healthcare
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1148/radiol.2019182908openalex-snapshot
A Deep Learning Model to Triage Screening Mammograms: A Simulation Study
inferredcites →https://doi.org/10.1148/radiol.2020201874openalex-snapshot
COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System
inferredcites →https://doi.org/10.1155/2018/8923028openalex-snapshot
Fully Automated Delineation of Gross Tumor Volume for Head and Neck Cancer on PET-CT Using Deep Learning: A Dual-Center Study
inferredcites →https://doi.org/10.1158/0008-5472.can-17-0313openalex-snapshot
Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis
inferredcites →https://doi.org/10.1158/0008-5472.can-17-0323openalex-snapshot
An Image Analysis Resource for Cancer Research: PIIP—Pathology Image Informatics Platform for Visualization, Analysis, and Management
inferredcites →https://doi.org/10.1158/1078-0432.ccr-17-0151openalex-snapshot
Intra- and Interobserver Reproducibility Assessment of PD-L1 Biomarker in Non–Small Cell Lung Cancer
inferredcites →https://doi.org/10.1158/1078-0432.ccr-18-2495openalex-snapshot
Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging
inferredcites →https://doi.org/10.1158/1078-0432.ccr-20-2415openalex-snapshot
Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma
inferredcites →https://doi.org/10.1158/1538-7445.am2017-661openalex-snapshot
Abstract 661: Evaluating "harmonization" of PD-L1 assays using image analysis
inferredcites →https://doi.org/10.1158/1538-7445.am2019-4700openalex-snapshot
Abstract 4700: Quantification of intratumoral heterogeneity in individual luminal A breast cancers from whole transcriptome data through semi-supervised learning
inferredcites →https://doi.org/10.1158/2326-6066.cir-16-0148openalex-snapshot
Infiltration of CD8 T Cells and Expression of PD-1 and PD-L1 in Synovial Sarcoma
inferredcites →https://doi.org/10.1183/13993003.00986-2018openalex-snapshot
Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning
inferredcites →https://doi.org/10.1186/1471-2407-10-640openalex-snapshot
Evaluation of FTIR Spectroscopy as a diagnostic tool for lung cancer using sputum
inferredcites →https://doi.org/10.1186/s12880-020-00505-zopenalex-snapshot
Interobserver variability in quality assessment of magnetic resonance images
inferredcites →https://doi.org/10.1186/s12885-019-5392-zopenalex-snapshot
Quantification of intrinsic subtype ambiguity in Luminal A breast cancer and its relationship to clinical outcomes
inferredcites →https://doi.org/10.1186/s12911-017-0468-7openalex-snapshot
Entity recognition from clinical texts via recurrent neural network
inferredcites →https://doi.org/10.1186/s13058-020-1248-3openalex-snapshot
A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival
inferredcites →https://doi.org/10.1200/cci.18.00157openalex-snapshot
HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides
inferredcites →https://doi.org/10.1200/cci.19.00126openalex-snapshot
Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data
inferredcites →https://doi.org/10.1200/jco.2020.38.15_suppl.3106openalex-snapshot
Deep learning-based predictive imaging biomarker model for EGFR mutation status in non-small cell lung cancer from CT imaging.
inferredcites →https://doi.org/10.14245/ns.1938396.198openalex-snapshot
Deep Learning in Medical Imaging
inferredcites →https://doi.org/10.14711/thesis-991012535962503412openalex-snapshot
Distant domain transfer learning
inferredcites →https://doi.org/10.1609/aaai.v31i1.10826openalex-snapshot
Distant Domain Transfer Learning
inferredcites →https://doi.org/10.17863/cam.38755openalex-snapshot
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
inferredcites →https://doi.org/10.21037/tlcr.2017.10.05openalex-snapshot
The reproducibility of PD-L1 scoring in lung cancer: can the pathologists do better?
inferredcites →https://doi.org/10.2172/1525811openalex-snapshot
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks
inferredcites →https://doi.org/10.3322/caac.21552openalex-snapshot
Artificial intelligence in cancer imaging: Clinical challenges and applications
inferredcites →https://doi.org/10.3389/fncom.2020.00010openalex-snapshot
A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas
inferredcites →https://doi.org/10.3389/fncom.2020.00061openalex-snapshot
Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning
inferredcites →https://doi.org/10.3389/fonc.2020.00028openalex-snapshot
Radiomics Signature as a Predictive Factor for EGFR Mutations in Advanced Lung Adenocarcinoma
inferredcites →https://doi.org/10.3390/cancers11010111openalex-snapshot
A Review on a Deep Learning Perspective in Brain Cancer Classification
inferredcites →https://doi.org/10.3390/diagnostics9030072openalex-snapshot
Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm
inferredcites →https://doi.org/10.3390/s18092799openalex-snapshot
Breast Cancer Detection Using Infrared Thermal Imaging and a Deep Learning Model
inferredcites →https://doi.org/10.3747/co.v15i6.242openalex-snapshot
Residual Cancer Burden in Locally Advanced Breast Cancer: A Superior Tool
inferredcites →https://doi.org/10.3758/app.72.5.1205openalex-snapshot
Current perspectives in medical image perception
inferredcites →https://doi.org/10.4103/0971-3026.111468openalex-snapshot
Vendor neutral archive in PACS
inferredcites →https://doi.org/10.4103/2153-3539.119005openalex-snapshot
OpenSlide: A vendor-neutral software foundation for digital pathology
inferredcites →https://doi.org/10.4103/jpi.jpi_10_20openalex-snapshot
Deep Learning to Estimate Human Epidermal Growth Factor Receptor 2 Status from Hematoxylin and Eosin-Stained Breast Tissue Images
inferredcites →https://doi.org/10.4230/lipics.ecoop.2020.15openalex-snapshot
Static Analysis of Shape in TensorFlow Programs
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.4258/hir.2019.25.4.324openalex-snapshot
PACS Implementation Challenges in a Public Healthcare Institution: A South African Vendor Perspective
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1411.1792openalex-snapshot
How transferable are features in deep neural networks?
inferredcites →https://doi.org/10.48550/arxiv.1412.7062openalex-snapshot
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
inferredcites →https://doi.org/10.48550/arxiv.1511.08630openalex-snapshot
A C-LSTM Neural Network for Text Classification
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
inferredcites →https://doi.org/10.48550/arxiv.1606.05718openalex-snapshot
Deep Learning for Identifying Metastatic Breast Cancer
inferredcites →https://doi.org/10.48550/arxiv.1711.05775openalex-snapshot
End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design
inferredcites →https://doi.org/10.48550/arxiv.1712.04621openalex-snapshot
The Effectiveness of Data Augmentation in Image Classification using Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1802.04712openalex-snapshot
Attention-based Deep Multiple Instance Learning
inferredcites →https://doi.org/10.48550/arxiv.1805.07836openalex-snapshot
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
inferredcites →https://doi.org/10.52202/079017openalex-snapshot
Advances in Neural Information Processing Systems 37
inferredcites →https://doi.org/10.5858/arpa.2018-0343-raopenalex-snapshot
A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association
inferredcites →https://doi.org/10.7326/0003-4819-149-10-200811180-00009openalex-snapshot
Assessing the Value of Risk Predictions by Using Risk Stratification Tables
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/hsr2.72884openalex-snapshot
Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review
inferred← citeshttps://doi.org/10.1007/978-3-031-96899-0_8openalex-snapshot
A Comparative Study of Deep Neural Network Architectures in Magnification Invariant Breast Cancer Histopathology Image Analysis
inferred← citeshttps://doi.org/10.1016/j.clon.2023.09.013openalex-snapshot
Imaging Analytics using Artificial Intelligence in Oncology: A Comprehensive Review
inferred← citeshttps://doi.org/10.1109/access.2024.3445954openalex-snapshot
ST-Double-Net: A Two-Stage Breast Tumor Classification Model Based on Swin Transformer and Weakly Supervised Target Localization
inferred← citeshttps://doi.org/10.1109/access.2024.3519216openalex-snapshot
A Synergistic Approach to Colon Cancer Detection: Leveraging EfficientNet and NSGA-II for Enhanced Diagnostic Performance
inferred← citeshttps://doi.org/10.1109/bibe55377.2022.00027openalex-snapshot
Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentation
inferred← citeshttps://doi.org/10.1109/bibe60311.2023.00027openalex-snapshot
Robust Semi-Supervised Learning for Histopathology Images Through Self-Supervision Guided Out-of-Distribution Scoring
inferred← citeshttps://doi.org/10.1109/embc46164.2021.9630477openalex-snapshot
Robust Classification of Histology Images Exploiting Adversarial Auto Encoders
inferred← citeshttps://doi.org/10.1109/icetea64585.2025.11099639openalex-snapshot
Optimized CNN Architecture Using Bio-Inspired and Computing for Lung Cancer Detection in Infrared Images
inferred← citeshttps://doi.org/10.1109/isbi52829.2022.9761682openalex-snapshot
Improved Histology Image Classification under Label Noise Via Feature Aggregating Memory Banks
inferred← citeshttps://doi.org/10.1109/isbi60581.2025.10981028openalex-snapshot
Pathogen-X: A Cross-Modal Genomic Feature Trans-Align Network for Enhanced Survival Prediction from Histopathology Images
inferred← citeshttps://doi.org/10.1615/critrevoncog.2023047799openalex-snapshot
Advanced Techniques in Head and Neck Cancer Imaging: Guide to Precision Cancer Management
inferred← citeshttps://doi.org/10.3233/jifs-213212openalex-snapshot
Research on classification algorithm of cerebral small vessel disease based on convolutional neural network
inferred← citeshttps://doi.org/10.3389/fonc.2022.1077341openalex-snapshot
Editorial: The use of deep learning in mapping and diagnosis of cancers
inferred← citeshttps://doi.org/10.3390/ijms26020477openalex-snapshot
Overview and Prospects of DNA Sequence Visualization
inferred← citeshttps://doi.org/10.3390/pharmaceutics16020260openalex-snapshot
Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges
inferred← citeshttps://doi.org/10.37349/etat.2023.00158openalex-snapshot
Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer
inferred← citeshttps://doi.org/10.37349/etat.2023.00159openalex-snapshot
Deep learning based clinico-radiological model for paediatric brain tumor detection and subtype prediction
inferred← citeshttps://doi.org/10.37349/etat.2024.00248openalex-snapshot
Correction: Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer
inferred← citeshttps://doi.org/10.4018/979-8-3693-8789-4.ch015openalex-snapshot
Exploring the Role of Deep Learning in Image Analysis for Breast Cancer Diagnosis
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.