mlsanityData to 7 Oct 2026

Language Models are Few-shot Learners for Prognostic Prediction

arXiv 2302.12692 ↗First posted 24 Feb 2023cs.CL cs.AI cs.LGcited by 37

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Abstract (arXiv)

Clinical prediction is an essential task in the healthcare industry. However, the recent success of transformers, on which large language models are built, has not been extended to this domain. In this research, we explore the use of transformers and language models in prognostic prediction for immunotherapy using real-world patients' clinical data and molecular profiles. This paper investigates the potential of transformers to improve clinical prediction compared to conventional machine learning approaches and addresses the challenge of few-shot learning in predicting rare disease areas. The study benchmarks the efficacy of baselines and language models on prognostic prediction across multiple cancer types and investigates the impact of different pretrained language models under few-shot regimes. The results demonstrate significant improvements in accuracy and highlight the potential of NLP in clinical research to improve early detection and intervention for different diseases.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). Builds on 20 of its 37 references that are in the map. First posted on arXiv 24 Feb 2023.

Builds on

20 of 37 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  6. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  7. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  8. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  9. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
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  11. 2019Publicly Available Clinical BERT Embeddingscited by 995
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8 more
  1. 2021ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biasescited by 484
  2. 2020TabTransformer: Tabular Data Modeling Using Contextual Embeddingscited by 398
  3. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 395
  4. 2016DeepSurv: Personalized Treatment Recommender System Using A Cox Proportional Hazards Deep Neural Networkcited by 354
  5. 2022TabLLM: Few-shot Classification of Tabular Data with Large Language Modelscited by 273
  6. 2022Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Againcited by 83
  7. 2022Masked Image Modeling Advances 3D Medical Image Analysiscited by 71
  8. 2021GPT-3 Models are Poor Few-Shot Learners in the Biomedical Domaincited by 36

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Citing papers per year: 2023: 25; 2024: 6; 2025: 5; 2026: 1.

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  1. 2023Evaluating Object Hallucination in Large Vision-Language Modelscited by 1,696
  2. 2023Can We Edit Factual Knowledge by In-Context Learning?cited by 284
  3. 2023RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Modelcited by 180
  4. 2023Large language models in healthcare and medical domain: A reviewcited by 126
  5. 2023GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extractioncited by 116
  6. 2023Zero-Shot Listwise Document Reranking with a Large Language Modelcited by 81
  7. 2023LLMCad: Fast and Scalable On-device Large Language Model Inferencecited by 45
  8. 2023MoT: Memory-of-Thought Enables ChatGPT to Self-Improvecited by 37
  9. 2023Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Promptingcited by 33
  10. 2023Prompting Large Language Models for Topic Modelingcited by 24
  11. 2024ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notescited by 22
  12. 2023Beyond Prompts: Exploring the Design Space of Mixed-Initiative Co-Creativity Systemscited by 20
25 more
  1. 2023UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?cited by 14
  2. 2023LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialtiescited by 10
  3. 2024MemeCraft: Contextual and Stance-Driven Multimodal Meme Generationcited by 9
  4. 2024From Text to Multimodality: Exploring the Evolution and Impact of Large Language Models in Medical Practicecited by 8
  5. 2024AAD-LLM: Adaptive Anomaly Detection Using Large Language Modelscited by 7
  6. 2023Implicit Ray-Transformers for Multi-view Remote Sensing Image Segmentationcited by 6
  7. 2023Multi-hop Commonsense Knowledge Injection Framework for Zero-Shot Commonsense Question Answeringcited by 6
  8. 2023CCGen: Explainable Complementary Concept Generation in E-Commercecited by 5
  9. 2023PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Modelscited by 5
  10. 2024Quantifying Prediction Consistency Under Fine-Tuning Multiplicity in Tabular LLMscited by 5
  11. 2023Parameter-Efficient Learning for Text-to-Speech Accent Adaptationcited by 4
  12. 2023Soft Language Clustering for Multilingual Model Pre-trainingcited by 4
  13. 2025RAAD-LLM: Adaptive Anomaly Detection Using LLMs and RAG Integrationcited by 4
  14. 2023disco: a toolkit for Distributional Control of Generative Modelscited by 3
  15. 2023Understanding Parameter Sharing in Transformerscited by 3
  16. 2023Ask Language Model to Clean Your Noisy Translation Datacited by 3
  17. 2025Benchmarking Foundation Models and Parameter-Efficient Fine-Tuning for Prognosis Prediction in Medical Imagingcited by 3
  18. 2023Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehensioncited by 1
  19. 2023Life Regression based Patch Slimming for Vision Transformerscited by 1
  20. 2023Combining Language Models For Specialized Domains: A Colorful Approachcited by 1
  21. 2024Numbers Matter! Bringing Quantity-awareness to Retrieval Systemscited by 1
  22. 2025Evaluating Large Language Models for Automated Clinical Abstraction in Pulmonary Embolism Registries: Performance Across Model Sizes, Versions, and Parameterscited by 1
  23. 2025Advances in Large Language Models for Medicinecited by 1
  24. 2025Objective Metrics for Evaluating Large Language Models Using External Data Sourcescited by 0
  25. 2026Large Language Models are Approximate Survival Estimatorscited by 0