Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:47:36.994563Z
Paper Citation Record · LEDGER
As of 21 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2504.17279.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:47:36.994563Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
55 of 55 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 802bee73-0988-4dd7-b678-4390c5d36756 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Artificial intelligence in healthcare: past, present and future,
Reference 1
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Automated diagnosing primary open- angle glaucoma from fundus image by simulating human’s grad- ing with deep learning,
Reference 3
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Reference 4
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation ScholarChemQA: Unveiling the Power of Language Models in Chemical Research Question Answering
Reference 5
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Nature of metal-support interaction for metal catalysts on oxide supports,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Dis- secting racial bias in an algorithm used to manage the health of populations,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Chexclusion: Fairness gaps in deep chest x-ray classifiers,
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Reference 9
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Improving model fairness in image-based computer-aided diagnosis,
Reference 10
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR
Reference 12
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Fairness of classifiers across skin tones in dermatology,
Reference 13
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Observation 5d86d166-ef1b-4fe4-997b-77d852cfe848 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served populations,
Reference 14
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Observation af8b0c56-4864-4cd0-9596-a0ed30ea7fef · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Ethical analysis to im- prove decision-making on health technologies,
Reference 15
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Observation 59cd2744-a402-41c7-85a2-844631e1dbe2 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation On the ethics of algorithmic decision- making in healthcare,
Reference 16
Source-reported events for the cited work
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Observation 79885b1f-5fb8-4a88-9047-78aa10fe0da9 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Improving the fairness of chest x-ray classifiers,
Reference 17
Source-reported events for the cited work
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Observation 58a016aa-6c8a-4613-b9fc-e7c4c8bd19be · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Fairness without demographics through adversarially 11 reweighted learning,
Reference 18
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Observation 8d6209fc-437d-491c-9eac-8d1e0dc79294 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Pairwise fairness for ranking and regression,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation The limits of fair medical imaging ai in real-world generaliza- tion,
Reference 20
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation An extensive benchmark study on biomed- ical text generation and mining with chatgpt,
Reference 21
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Chatgpt in healthcare: a taxonomy and systematic review,
Reference 22
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Observation 45a0a6a7-d8c8-4e8b-9d3b-5229121a1ce1 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Opportunities and chal- lenges for chatgpt and large language models in biomedicine and health,
Reference 23
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Interactive and explainable region-guided radiology report generation,
Reference 24
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Observation d39ee8ac-56fe-4cbf-b636-d4baceca2ec0 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Radadapt: Radiology report summarization via lightweight domain adaptation of large language models,
Reference 25
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation The advent of generative language models in medical education,
Reference 26
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Observation f2a1a8e0-7ae6-4deb-869a-ca3ee29b3df7 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation The next generation of evidence-based medicine,
Reference 27
Source-reported events for the cited work
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Observation 7fe0dd61-1fee-479c-8e2e-4b9bea6cbe58 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Ethical and social risks of harm from Language Models
Reference 28
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Observation 0c539f9c-c7c2-4c08-9c22-736676b66432 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Smartphone-based conversational agents and responses to questions about mental health, interpersonal violence, and physical health,
Reference 29
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Patient and consumer safety risks when using conversational assistants for medical information: an observational study of siri, alexa, and google assistant,
Reference 30
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Observation 400cefc3-f8ed-4c16-9f65-6050715dcec3 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Auto- mated radiology report generation: A review of recent advances,
Reference 31
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Observation 8f92c88a-3e76-4d48-ad83-cbc11215b188 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation A survey on automatic generation of medical imaging reports based on deep learning,
Reference 32
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Bertscore: Evaluating text generation with bert,
Reference 33
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Observation b5fb8a10-e4c6-49c5-96b1-d7d4998778ae · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Evaluation of Text Generation: A Survey
Reference 34
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Observation fab41579-a16e-4e02-af1a-d1f061f1ddaf · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation GPTScore: Evaluate as You Desire
Reference 35
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Rouge: A package for automatic evaluation of sum- maries,
Reference 36
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Flexible and adaptable summarization via expertise separation,
Reference 37
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Revisiting the gold standard: Grounding summarization evaluation with robust human evaluation,
Reference 38
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Observation 59707875-48e0-4d6e-b418-f6f535070b36 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Questeval: Summarization asks for fact-based evaluation,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark
Reference 40
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Chexpert: A large chest radiograph dataset with uncertainty labels and ex- pert comparison,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation CXPMRG-Bench: Pre-training and Benchmarking for X-ray Medical Report Generation on CheXpert Plus Dataset
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Retrieval-based chest x-ray report generation using a pre-trained contrastive language-image model,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Baselines for chest x-ray report generation,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Generating radiology reports via memory-driven transformer,
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Bart: Denoising sequence-to-sequence pre-training for natural language genera- tion, translation, and comprehension,
Reference 46
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Evaluating and Mitigating Bias in AI-Based Medical Text Generation Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 47
Source-reported events for the cited work
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Observation c13400d7-6543-429b-b8a0-9b44d8ed8789 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs
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Source-reported events for the cited work
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Observation b60723c7-2d8f-4ff4-87dc-7dd140f5be14 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation A discourse-aware attention model for ab- stractive summarization of long documents,
Reference 49
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Observation 2717f0b2-a405-4f12-9709-7bf138f31f75 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Mimic-iv,
Reference 50
Source-reported events for the cited work
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Observation 8ada47c1-dd9a-487a-99c1-6747fc3d7b99 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Do hospitals provide lower quality of care to black patients for pneumonia?
Reference 51
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Observation 314d684b-4101-4aae-b5b5-542e93ce1e64 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Transformers: 12 State-of-the-art natural language processing,
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Observation 6187bc38-c8a1-4a20-aa1f-bb89c8b5bb66 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Deep residual learning for image recognition,
Reference 53
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Observation 0d444465-f031-4788-9d46-3b2a1a2b81eb · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Im- agenet: A large-scale hierarchical image database,
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Source-reported events for the cited work
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Observation 12a7af64-c687-4dc0-ba8e-599147db0480 · outbound
Evaluating and Mitigating Bias in AI-Based Medical Text Generation Adam: A Method for Stochastic Optimization
Reference 55
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.