mlsanityData to 7 Oct 2026

Foundation Model for Advancing Healthcare: Challenges, Opportunities, and Future Directions

arXiv 2404.03264 ↗First posted 4 Apr 2024cs.CY cs.AIcited by 77

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Abstract (arXiv)

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range of tasks, is advancing healthcare. It promotes the development of healthcare artificial intelligence (AI) models, breaking the contradiction between limited AI models and diverse healthcare practices. Much more widespread healthcare scenarios will benefit from the development of a healthcare foundation model (HFM), improving their advanced intelligent healthcare services. Despite the impending widespread deployment of HFMs, there is currently a lack of clear understanding about how they work in the healthcare field, their current challenges, and where they are headed in the future. To answer these questions, a comprehensive and deep survey of the challenges, opportunities, and future directions of HFMs is presented in this survey. It first conducted a comprehensive overview of the HFM including the methods, data, and applications for a quick grasp of the current progress. Then, it made an in-depth exploration of the challenges present in data, algorithms, and computing infrastructures for constructing and widespread application of foundation models in healthcare. This survey also identifies emerging and promising directions in this field for future development. We believe that this survey will enhance the community's comprehension of the current progress of HFM and serve as a valuable source of guidance for future development in this field. The latest HFM papers and related resources are maintained on our website: https://github.com/YutingHe-list/Awesome-Foundation-Models-for-Advancing-Healthcare.

Key facts. Cited by 77 papers in the map (data through 7 Oct 2026). Builds on 158 of its 287 references that are in the map. First posted on arXiv 4 Apr 2024.

Builds on

158 of 287 references.

References · 158

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38 more
  1. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  2. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
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50 most cited of 158 All 158 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 16; 2025: 36; 2026: 25.

77 papers.

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  1. 2024Continual Learning of Large Language Models: A Comprehensive Surveycited by 228
  2. 2025Multimodal Chain-of-Thought Reasoning: A Comprehensive Surveycited by 176
  3. 2025MedSAM2: Segment Anything in 3D Medical Images and Videoscited by 88
  4. 2024A Comprehensive Survey of Foundation Models in Medicinecited by 56
  5. 2024Large-Scale 3D Medical Image Pre-training with Geometric Context Priorscited by 34
  6. 2025MIRA: Medical Time Series Foundation Model for Real-World Health Datacited by 21
  7. 2025HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Seriescited by 19
  8. 2024MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysiscited by 17
  9. 2024A Survey on Large Language Models from General Purpose to Medical Applications: Datasets, Methodologies, and Evaluationscited by 16
  10. 2024A Survey on Trustworthiness in Foundation Models for Medical Image Analysiscited by 16
  11. 2025Deep Learning and Foundation Models for Weather Prediction: A Surveycited by 15
  12. 2024Towards a vision foundation model for comprehensive assessment of Cardiac MRIcited by 13
38 more
  1. 2025A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Modelcited by 12
  2. 2024EchoApex: A General-Purpose Vision Foundation Model for Echocardiographycited by 11
  3. 2024Pathology Foundation Modelscited by 7
  4. 2024MedConceptsQA: Open Source Medical Concepts QA Benchmarkcited by 6
  5. 2025FoMoH: A clinically meaningful foundation model evaluation for structured electronic health recordscited by 6
  6. 2025From large language models to multimodal AI: A scoping review on the potential of generative AI in medicinecited by 5
  7. 2025Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomicscited by 5
  8. 2026Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directionscited by 5
  9. 2024QUB-Cirdan at "Discharge Me!": Zero shot discharge letter generation by open-source LLMcited by 4
  10. 2025Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learningcited by 4
  11. 2025Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoningcited by 4
  12. 2025Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025cited by 4
  13. 2025Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Datacited by 3
  14. 2025SingLEM: Single-Channel Large EEG Modelcited by 3
  15. 2025Adaptation of Foundation Models for Medical Image Analysis: Strategies, Challenges, and Future Directionscited by 3
  16. 2026HyperFM: An Efficient Hyperspectral Foundation Model with Spectral Groupingcited by 3
  17. 2026Medical world models in healthcare: foundations, applications, and challenges for trustworthy clinical translationcited by 3
  18. 2024Anatomy-Guided Radiology Report Generation with Pathology-Aware Regional Promptscited by 2
  19. 2024LaB-RAG: Label Boosted Retrieval Augmented Generation for Radiology Report Generationcited by 2
  20. 2025Foundation Model for Whole-Heart Segmentation: Leveraging Student-Teacher Learning in Multi-Modal Medical Imagingcited by 2
  21. 2025On the Performance of an Explainable Language Model on PubMedQAcited by 2
  22. 2025Generalist Models in Medical Image Segmentation: A Survey and Performance Comparison with Task-Specific Approachescited by 2
  23. 2025Vector Contrastive Learning For Pixel-Wise Pretraining In Medical Visioncited by 2
  24. 2025MedIQA: A Scalable Foundation Model for Prompt-Driven Medical Image Quality Assessmentcited by 2
  25. 2025MedPatch: Confidence-Guided Multi-Stage Fusion for Multimodal Clinical Datacited by 2
  26. 2025FairTune: A Bias-Aware Fine-Tuning Framework Towards Fair Heart Rate Prediction from PPGcited by 2
  27. 2025Towards Generalist Intelligence in Dentistry: Vision Foundation Models for Oral and Maxillofacial Radiologycited by 2
  28. 2026A data- and compute-efficient chest X-ray foundation model beyond aggressive scalingcited by 2
  29. 2026Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attributioncited by 2
  30. 2026Learning Clinical Representations Under Systematic Distribution Shiftcited by 2
  31. 2026Discriminative Representation Learning for Clinical Predictioncited by 2
  32. 2024Nuclear Medicine AI in Action: The Bethesda Report (AI Summit 2024)cited by 1
  33. 2024DSCENet: Dynamic Screening and Clinical-Enhanced Multimodal Fusion for MPNs Subtype Classificationcited by 1
  34. 2025Feedback-Driven Vision-Language Alignment with Minimal Human Supervisioncited by 1
  35. 2025In-Context Learning for Label-Efficient Cancer Image Classification in Oncologycited by 1
  36. 2025Multimodal Foundation Models for Early Disease Detectioncited by 1
  37. 2026Learning Longitudinal Health Representations from EHR and Wearable Datacited by 1
  38. 2026Uncertainty-Aware Foundation Models for Clinical Datacited by 1

50 most cited of 77 All 77 (JSON)