Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription | Paper Citation Record

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Heterogeneous data and big data analytics,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Language models are unsupervised multitask learners,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Language Models are Few-Shot Learners

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Sparks of Artificial General Intelligence: Early experiments with GPT-4

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Winogrande: An adversarial winograd schema challenge at scale,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Language mod- els are few-shot learners,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Zero-shot clinical trial patient matching with LLMs

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription How fine-tuning allows for effective meta-learning,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Robust fine-tuning of deep neural net- works with hessian-based generalization guarantees,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Lexfit: Lexical fine-tuning of pretrained language models,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Revisiting Few-sample BERT Fine-tuning

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Position paper: On the societal impact of open foundation models,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Foundation models in healthcare: Opportunities, risks & strategies forward,

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This paper cites Attention is all you need,.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Attention is all you need,

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This paper cites A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics

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This paper cites On the Opportunities and Risks of Foundation Models.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription On the Opportunities and Risks of Foundation Models

Reference 20

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The gradient of generative AI release: Methods and considerations,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Code Llama: Open Foundation Models for Code

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Competition in generative artificial intelligence founda- tion models,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription D2. 6: Ontology of licencing, ownership and conditions of use (v1. 0),

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The open source definition (osd),

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription DiBona and S

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Llama 2: Open Foundation and Fine-Tuned Chat Models

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription On the societal impact of open foundation models,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Accelerating LLM Inference with Staged Speculative Decoding

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Extracting training data from large language models,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription On the dangers of stochastic parrots: Can language models be too big?

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Adversarial Attacks Against Medical Deep Learning Systems

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Adversarial attacks on medical machine learning,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Generalizability vs. Robustness: Adversarial Examples for Medical Imaging

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Deep learning models for electrocardiograms are susceptible to adversarial attack,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Ethical considerations of using ChatGPT in health care,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Re- enacting machine learning practices to enquire into the moral issues they pose,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription HIPAA, HIPPA, or HIPPO: What really is the heath in- surance portability and accountability act?

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The european general data protection regulation (GDPR) in mhealth: Theoretical and practical aspects for practitioners’ use,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Chain-of-thought prompting elicits reasoning in large language models,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Learning transferable visual models from natural language supervision,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription A foundation model for generalizable disease detection from retinal images,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Lvm-med: Learn- ing large-scale self-supervised vision models for medical imaging via second-order graph matching,

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription GLORIA-A globally representative hyperspectral in situ dataset for optical sensing of water quality,

Reference 55

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

Reference 56

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription PLIP: Language-Image Pre-training for Person Representation Learning

Reference 57

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Observation de69e0e3-d16c-4ffd-bf58-5cfac2ac2f43 · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Praveen and V

Reference 58

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription An Analysis on Large Language Models in Healthcare: A Case Study of BioBERT

Reference 59

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatGPT: Is this version good for healthcare and research?

Reference 60

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The future landscape of large language models in medicine,

Reference 61

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The shaky foundations of large language models and foundation models for electronic health records,

Reference 62

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement

Reference 63

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Ehr foundation models improve robustness in the presence of temporal distribution shift,

Reference 64

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Large language models encode clinical knowledge,

Reference 65

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription DeID-GPT: zero-shot medical text de- identification by GPT-4,

Reference 66

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Observation 68bbf35d-50b8-4ff5-9e00-f7d588874c08 · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription GPT-4: a new era of artificial intelligence in medicine,

Reference 67

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatGPT and Large Language Models (LLMs) in Healthcare: Opportunities and Risks,

Reference 68

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Domain-specific language model pretraining for biomedical natural language processing,

Reference 69

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Observation b145ddc4-2660-4a62-a73f-c0b2791b5796 · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

Reference 70

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This paper cites Conversational AI models for ophthalmic diagnosis: Comparison of ChatGPT and the Isabel pro differential diagnosis generator,.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Conversational AI models for ophthalmic diagnosis: Comparison of ChatGPT and the Isabel pro differential diagnosis generator,

Reference 71

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Observation aeabda48-982a-4585-8dc2-b47eac9a8809 · outbound

This paper cites The diagnostic and triage accuracy of the GPT-3 artificial intelligence model,.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The diagnostic and triage accuracy of the GPT-3 artificial intelligence model,

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-09T11:34:08.896856Z

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Observation 283eebe5-31e7-4321-802b-78c12f882de6 · outbound

This paper cites Faithful AI in Medicine: A Systematic Review with Large Language Models and Beyond,.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Faithful AI in Medicine: A Systematic Review with Large Language Models and Beyond,

Reference 73

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Observation 8add64a5-578c-4a1d-8b40-ed76588fd061 · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatGPT and the future of medical writing,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-09T11:34:08.905132Z

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This paper cites Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

Reference 75

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning

Reference 76

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Observation 8e6b0fcd-2f2f-42b7-b13e-f757114032fa · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Clinical applications of deep learning in breast MRI,

Reference 77

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This paper cites Pancreatic cancer detection on CT scans with deep learning: a nationwide population-based study,.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Pancreatic cancer detection on CT scans with deep learning: a nationwide population-based study,

Reference 78

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Observation 08851527-748e-4b89-8bc1-901e89c0793d · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Capabilities of GPT-4 on Medical Challenge Problems

Reference 79

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Observation f546d644-db94-4ff0-a6b5-ae940856e6ae · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Artificial General Intelligence for Medical Imaging Analysis

Reference 80

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription On the Challenges and Perspectives of Foundation Models for Medical Image Analysis

Reference 81

Resolution: verified exact; local_arxiv, observed 2026-08-09T11:34:10.173417Z

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This paper cites Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation,.

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation,

Reference 82

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications

Reference 83

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery

Reference 84

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Implications of large language models such as ChatGPT for dental medicine,

Reference 85

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers,

Reference 86

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models,

Reference 87

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Van Bulck and P

Reference 88

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription A Review of ChatGPT Applications in Education, Marketing, Software Engineering, and Healthcare: Benefits, Drawbacks, and Research Directions

Reference 89

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Observation 17800303-4a2e-45d5-b573-bc7b4250c757 · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Large language models in medical education: Opportunities, challenges, and future directions,

Reference 90

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Im- proved performance of ChatGPT-4 on the OKAP exam: A comparative study with ChatGPT-3.5,

Reference 91

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Evaluating the performance of ChatGPT in ophthalmology: An analysis of its successes and shortcomings,

Reference 92

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatGPT: Vision and challenges,

Reference 93

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription AI-based large language models are ready to transform psychological health assessment,

Reference 94

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatGPT in healthcare: A taxonomy and systematic review,

Reference 95

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatGPT: A comprehensive review on background, ap- plications, key challenges, bias, ethics, limitations and future scope,

Reference 96

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Observation 6b18d5e3-143a-41f5-9a13-ebbd3073406e · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge

Reference 97

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription Chatdoctor: A medical chat model fine-tuned on a large language model meta-ai (llama) using medical domain knowledge,

Reference 98

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Observation 8f979cb6-70c9-4c37-b147-26304a64975c · outbound

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription PMC-LLaMA: Towards Building Open-source Language Models for Medicine

Reference 99

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Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription AI-generated medical advice—GPT and beyond,

Reference 100

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