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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Evaluating Pneumonia Classification Robustness Across Architectures Under Variable-Quality Chest Radiographs
inferred← citeshttps://doi.org/10.1007/978-3-658-29267-6_64openalex-snapshot
Epoch-Wise Label Attacks for Robustness Against Label Noise
inferred← citeshttps://doi.org/10.1007/978-3-658-33597-7_29openalex-snapshot
Künstliche Intelligenz in der Radiologie und Strahlentherapie aus der Perspektive von Ärzten und Medizinphysikexperten – Eine Interviewstudie
inferred← citeshttps://doi.org/10.1007/978-3-658-33597-7_35openalex-snapshot
Erklärbare KI in der medizinischen Diagnose – Erfolge und Herausforderungen
inferred← citeshttps://doi.org/10.1007/978-3-658-43860-9_34openalex-snapshot
Künstliche Intelligenz Technologie in der Radiologie: Eine systematische Überprüfung von KI-Anwendungsfällen
inferred← citeshttps://doi.org/10.1007/978-981-15-3984-8_9openalex-snapshot
Deep Learning for Image Processing and Reconstruction to Enhance LED-Based Photoacoustic Imaging
inferred← citeshttps://doi.org/10.1007/978-981-16-9447-9_55openalex-snapshot
Breast Cancer Mammography Identification with Deep Convolutional Neural Network
inferred← citeshttps://doi.org/10.1007/978-981-19-2057-8_15openalex-snapshot
Computer-Aided Diagnosis of Pneumothorax Through X-Ray Images Using Deep Learning—A Review
inferred← citeshttps://doi.org/10.1007/978-981-19-3590-9_46openalex-snapshot
Implementation of Personalized Medicine by Artificial Intelligence Platform
inferred← citeshttps://doi.org/10.1007/978-981-19-4831-2_34openalex-snapshot
A Comparative Study of Machine Learning and Deep Learning Techniques on X-ray Images for Pneumonia
inferred← citeshttps://doi.org/10.1007/978-981-19-6880-8_16openalex-snapshot
Brain Tumor Segmentation Using U-Net
inferred← citeshttps://doi.org/10.1007/978-981-19-7455-7_21openalex-snapshot
Bone Cancer Detection Using Deep Learning
inferred← citeshttps://doi.org/10.1007/978-981-19-9379-4_58openalex-snapshot
Improving Pneumonia Detection Using Segmentation and Image Enhancement
inferred← citeshttps://doi.org/10.1007/978-981-92-3501-8_26openalex-snapshot
VCGNet: A Hybrid State-Space, CNN and Graph Framework for Multi-label Chest X-Ray Classification
inferred← citeshttps://doi.org/10.1007/978-981-95-1357-4_4openalex-snapshot
ECT-DLM: Deep Learning-Based Empirical Curvelet Transform Approach for Thoracic Disease Diagnosis from X-RAY Images
inferred← citeshttps://doi.org/10.1007/978-981-96-0434-0_11openalex-snapshot
Enhancing Efficiency of Multi-Label X-Ray Image Classification with Self-Supervised Learning Based On Compact Swin Transformers
inferred← citeshttps://doi.org/10.1007/978-981-96-3644-0_9openalex-snapshot
Comparison and Analysis for Pneumonia Detection Using Deep Learning Models
inferred← citeshttps://doi.org/10.1007/978-981-96-3863-5_6openalex-snapshot
Attention-Based CNN for Enhanced Detection of Arsenic Exposure
inferred← citeshttps://doi.org/10.1007/978-981-96-4360-8_14openalex-snapshot
Advanced Topics in Blockchain for Healthcare
inferred← citeshttps://doi.org/10.1007/978-981-96-5415-4_12openalex-snapshot
Interpretable Prediction Model for Chest X-Ray COVID-19 Diagnosis: A Comparative Assessment Using Grad-CAM, Occlusion Sensitivity, and LIME
inferred← citeshttps://doi.org/10.1007/978-981-96-6124-4_48openalex-snapshot
Exploring Pneumonia Detection Using Machine Learning Methods
inferred← citeshttps://doi.org/10.1007/978-981-96-6291-3_25openalex-snapshot
AI-Driven Classification of Chest Diseases Using X-Ray Images
inferred← citeshttps://doi.org/10.1007/978-981-96-6906-6_29openalex-snapshot
Enhanced Brain Tumor Detection Using Convolutional Neural Networks and YOLO V4 on MRI Images
inferred← citeshttps://doi.org/10.1007/978-981-96-7448-0_37-1openalex-snapshot
Artificial Intelligence in Orthopedics Research: From Diagnoses of Fractures to Interventions and Surgical Outcomes
inferred← citeshttps://doi.org/10.1007/978-981-96-9263-7_11openalex-snapshot
Frontiers of AI Technologies
inferred← citeshttps://doi.org/10.1007/978-981-97-2079-8_5openalex-snapshot
Exploring the Potential of Deep Learning Algorithms in Medical Image Processing: A Comprehensive Analysis
inferred← citeshttps://doi.org/10.1007/978-981-97-6352-8_37openalex-snapshot
Transfer Learning-Based Comparative Analysis of Lung Disease Prediction
inferred← citeshttps://doi.org/10.1007/978-981-97-7184-4_21openalex-snapshot
Confidence-Guided Online Knowledge Distillation for Semi-supervised Medical Image Classification
inferred← citeshttps://doi.org/10.1007/978-981-97-8496-7_20openalex-snapshot
Pseudo-Prompt Generating in Pre-trained Vision-Language Models for Multi-label Medical Image Classification
inferred← citeshttps://doi.org/10.1007/978-981-99-3966-4_1openalex-snapshot
Toward Behavioral AI: Cognitive Factors Underlying the Public Psychology of Artificial Intelligence
inferred← citeshttps://doi.org/10.1007/978-981-99-8296-7_3openalex-snapshot
Biggest Margin Tree for the Multi-class Classification
inferred← citeshttps://doi.org/10.1007/978-981-99-9489-2_6openalex-snapshot
Enhancing Trust in AI-Generated Medical Narratives: A Transparent Approach for Simplifying Radiology Reports
inferred← citeshttps://doi.org/10.1007/s00108-023-01604-zopenalex-snapshot
Künstliche Intelligenz in der internistischen Versorgung
inferred← citeshttps://doi.org/10.1007/s00117-022-01097-1openalex-snapshot
Validierung und Implementierung von künstlicher Intelligenz in der radiologischen Versorgung
inferred← citeshttps://doi.org/10.1007/s00120-020-01272-zopenalex-snapshot
Wie weit ist Chirugie 4.0?
inferred← citeshttps://doi.org/10.1007/s00138-020-01101-5openalex-snapshot
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
inferred← citeshttps://doi.org/10.1007/s00204-021-03188-9openalex-snapshot
Perspectives of future lung toxicology studies using human pluripotent stem cells
inferred← citeshttps://doi.org/10.1007/s00216-021-03179-wopenalex-snapshot
Spatially aware clustering of ion images in mass spectrometry imaging data using deep learning
inferred← citeshttps://doi.org/10.1007/s00223-022-01035-2openalex-snapshot
Contemporary Advances in Computer-Assisted Bone Histomorphometry and Identification of Bone Cells in Culture
inferred← citeshttps://doi.org/10.1007/s00234-026-04183-6openalex-snapshot
The impact of teleradiology: balancing clinical benefits and operational limitations
inferred← citeshttps://doi.org/10.1007/s00247-021-05146-0openalex-snapshot
Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective
inferred← citeshttps://doi.org/10.1007/s00247-025-06485-yopenalex-snapshot
Triage and workflow optimization with artificial intelligence in pediatric imaging
inferred← citeshttps://doi.org/10.1007/s00256-021-03880-yopenalex-snapshot
Can AI distinguish a bone radiograph from photos of flowers or cars? Evaluation of bone age deep learning model on inappropriate data inputs
inferred← citeshttps://doi.org/10.1007/s00256-025-04951-0openalex-snapshot
Optimizing the power of AI for fracture detection: from blind spots to breakthroughs
inferred← citeshttps://doi.org/10.1007/s00259-019-04374-9openalex-snapshot
Next generation research applications for hybrid PET/MR and PET/CT imaging using deep learning
inferred← citeshttps://doi.org/10.1007/s00259-021-05270-xopenalex-snapshot
Just another “Clever Hans”? Neural networks and FDG PET-CT to predict the outcome of patients with breast cancer
inferred← citeshttps://doi.org/10.1007/s00261-025-05016-5openalex-snapshot
Curriculum check, 2025—equipping radiology residents for AI challenges of tomorrow
inferred← citeshttps://doi.org/10.1007/s00264-024-06369-0openalex-snapshot
Can computer vision / artificial intelligence locate key reference points and make clinically relevant measurements on axillary radiographs?
inferred← citeshttps://doi.org/10.1007/s00266-021-02698-2openalex-snapshot
Assessment of an Artificial Intelligence Mandibular Osteotomy Design System: A Retrospective Study
inferred← citeshttps://doi.org/10.1007/s00292-020-00827-3openalex-snapshot
Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung
inferred← citeshttps://doi.org/10.1007/s00330-019-06205-9openalex-snapshot
Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI
inferred← citeshttps://doi.org/10.1007/s00330-019-06214-8openalex-snapshot
Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features
inferred← citeshttps://doi.org/10.1007/s00330-019-06589-8openalex-snapshot
Test-retest reproducibility of a deep learning–based automatic detection algorithm for the chest radiograph
inferred← citeshttps://doi.org/10.1007/s00330-019-06628-4openalex-snapshot
CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists
inferred← citeshttps://doi.org/10.1007/s00330-020-06771-3openalex-snapshot
Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study
inferred← citeshttps://doi.org/10.1007/s00330-020-07044-9openalex-snapshot
A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images
inferred← citeshttps://doi.org/10.1007/s00330-020-07062-7openalex-snapshot
Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration
inferred← citeshttps://doi.org/10.1007/s00330-020-07544-8openalex-snapshot
Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study
inferred← citeshttps://doi.org/10.1007/s00330-021-08162-8openalex-snapshot
Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial
inferred← citeshttps://doi.org/10.1007/s00330-022-08538-4openalex-snapshot
Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours
inferred← citeshttps://doi.org/10.1007/s00330-022-08752-0openalex-snapshot
Artificial intelligence-based detection of atrial fibrillation from chest radiographs
inferred← citeshttps://doi.org/10.1007/s00330-023-10124-1openalex-snapshot
Use of artificial intelligence in triaging of chest radiographs to reduce radiologists’ workload
inferred← citeshttps://doi.org/10.1007/s00405-025-09371-3openalex-snapshot
AI in clinical decision-making: ChatGPT-4 vs. Llama2 for otolaryngology cases
inferred← citeshttps://doi.org/10.1007/s00405-025-09925-5openalex-snapshot
Comparative diagnostic accuracy of ChatGPT models in salivary gland disease: a multimodal vignette-based evaluation
inferred← citeshttps://doi.org/10.1007/s00408-023-00655-1openalex-snapshot
An Artificial Intelligence Platform for the Radiologic Diagnosis of Pulmonary Sarcoidosis: An Initial Pilot Study of Chest Computed Tomography Analysis to Distinguish Pulmonary Sarcoidosis from a Negative Lung Cancer Screening Scan
inferred← citeshttps://doi.org/10.1007/s00464-021-08331-2openalex-snapshot
A novel machine learning-based algorithm to identify and classify lesions and anatomical landmarks in colonoscopy images
inferred← citeshttps://doi.org/10.1007/s00500-025-10644-6openalex-snapshot
Shadow learner system: implementation of CNN with explainable AI model for bone radiology image classification
inferred← citeshttps://doi.org/10.1007/s00521-023-08606-wopenalex-snapshot
BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data
inferred← citeshttps://doi.org/10.1007/s00521-023-09147-yopenalex-snapshot
A hybrid deep convolutional neural network model for improved diagnosis of pneumonia
inferred← citeshttps://doi.org/10.1007/s00521-023-09207-3openalex-snapshot
MLDC: multi-lung disease classification using quantum classifier and artificial neural networks
inferred← citeshttps://doi.org/10.1007/s00521-024-10527-1openalex-snapshot
Lung disease classification using deep learning and genetic algorithm
inferred← citeshttps://doi.org/10.1007/s00521-026-11847-0openalex-snapshot
A Comparative evaluation of deep learning-based capillaroscopy image analysis using YOLOv8–YOLOv12 models for microvascular diagnostics
inferred← citeshttps://doi.org/10.1007/s00595-022-02601-9openalex-snapshot
Surgery utilizing artificial intelligence technology: why we should not rule it out
inferred← citeshttps://doi.org/10.1007/s00740-026-00587-5openalex-snapshot
Künstliche Intelligenz in der Frakturerkennung
inferred← citeshttps://doi.org/10.1007/s00761-019-00679-4openalex-snapshot
Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung
inferred← citeshttps://doi.org/10.1007/s10044-026-01774-0openalex-snapshot
Multimodal learning for imbalanced multi-label chest X-ray classification with radiology reports
inferred← citeshttps://doi.org/10.1007/s10096-025-05317-zopenalex-snapshot
Artificial intelligence in clinical microbiology: results from the first National survey by the Italian association of clinical microbiologists
inferred← citeshttps://doi.org/10.1007/s10140-020-01767-4openalex-snapshot
Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax
inferred← citeshttps://doi.org/10.1007/s10140-021-01954-xopenalex-snapshot
Limited generalizability of deep learning algorithm for pediatric pneumonia classification on external data
inferred← citeshttps://doi.org/10.1007/s10140-022-02019-3openalex-snapshot
Deep learning prediction of sex on chest radiographs: a potential contributor to biased algorithms
inferred← citeshttps://doi.org/10.1007/s10278-019-00180-9openalex-snapshot
Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1007/s10278-021-00543-1openalex-snapshot
Chest Radiographs Using a Context-Fusion Convolution Neural Network (CNN): Can It Distinguish the Etiology of Community-Acquired Pneumonia (CAP) in Children?
inferred← citeshttps://doi.org/10.1007/s10278-023-00849-2openalex-snapshot
Enhancement of Non-Linear Deep Learning Model by Adjusting Confounding Variables for Bone Age Estimation in Pediatric Hand X-rays
inferred← citeshttps://doi.org/10.1007/s10278-023-00868-zopenalex-snapshot
Automated Rib Fracture Detection on Chest X-Ray Using Contrastive Learning
inferred← citeshttps://doi.org/10.1007/s10278-023-00882-1openalex-snapshot
Detecting and Characterizing Inferior Vena Cava Filters on Abdominal Computed Tomography with Data-Driven Computational Frameworks
inferred← citeshttps://doi.org/10.1007/s10278-024-00990-6openalex-snapshot
Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance
inferred← citeshttps://doi.org/10.1007/s10278-024-01005-0openalex-snapshot
Classification of Lung Diseases Using an Attention-Based Modified DenseNet Model
inferred← citeshttps://doi.org/10.1007/s10278-024-01136-4openalex-snapshot
Gradient-Based Saliency Maps Are Not Trustworthy Visual Explanations of Automated AI Musculoskeletal Diagnoses
inferred← citeshttps://doi.org/10.1007/s10278-024-01247-yopenalex-snapshot
Integrating VAI-Assisted Quantified CXRs and Multimodal Data to Assess the Risk of Mortality
inferred← citeshttps://doi.org/10.1007/s10278-024-01309-1openalex-snapshot
Applying Deep-Learning Algorithm Interpreting Kidney, Ureter, and Bladder (KUB) X-Rays to Detect Colon Cancer
inferred← citeshttps://doi.org/10.1007/s10278-025-01472-zopenalex-snapshot
Highly Accurate Occupational Pneumoconiosis Staging via Dark Channel Prior-Inspired Lesion Area Enhancement
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