# Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation

arXiv: https://arxiv.org/abs/2405.18346 · HTML: https://mlsanity.com/paper/2405.18346/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 43 references that are in the map.
- First posted on arXiv 28 May 2024.

## Builds on (most cited first, 9 of 9)

- [Measuring Massive Multitask Language Understanding](https://mlsanity.com/paper/2009.03300/) (2020)
- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams](https://mlsanity.com/paper/2009.13081/) (2020)
- [The NarrativeQA Reading Comprehension Challenge](https://mlsanity.com/paper/1712.07040/) (2017)
- [PromptChainer: Chaining Large Language Model Prompts through Visual Programming](https://mlsanity.com/paper/2203.06566/) (2022)
- [PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures](https://mlsanity.com/paper/2112.05135/) (2021)
- [End-to-end speaker segmentation for overlap-aware resegmentation](https://mlsanity.com/paper/2104.04045/) (2021)
- [LMDX: Language Model-based Document Information Extraction and Localization](https://mlsanity.com/paper/2309.10952/) (2023)
- [Boosted Prompt Ensembles for Large Language Models](https://mlsanity.com/paper/2304.05970/) (2023)

## Built on by (most cited first, 20 of 20)

- [Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers](https://mlsanity.com/paper/2504.18412/) (2025)
- [MedS3: Towards Medical Slow Thinking with Self-Evolved Soft Dual-sided Process Supervision](https://mlsanity.com/paper/2501.12051/) (2025)
- [ReflecTool: Towards Reflection-Aware Tool-Augmented Clinical Agents](https://mlsanity.com/paper/2410.17657/) (2024)
- [PersoBench: Benchmarking Personalized Response Generation in Large Language Models](https://mlsanity.com/paper/2410.03198/) (2024)
- [Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond](https://mlsanity.com/paper/2502.03945/) (2025)
- [The Extractive-Abstractive Spectrum: Uncovering Verifiability Trade-offs in LLM Generations](https://mlsanity.com/paper/2411.17375/) (2024)
- [Improving Clinical Note Generation from Complex Doctor-Patient Conversation](https://mlsanity.com/paper/2408.14568/) (2024)
- [H2HMem: A Multimodal Memory Benchmark for Agents in Human-Human Interactions](https://mlsanity.com/paper/2606.09461/) (2026)
- [CLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs](https://mlsanity.com/paper/2507.06715/) (2025)
- [AgentEHR: Advancing Autonomous Clinical Decision-Making via Retrospective Summarization](https://mlsanity.com/paper/2601.13918/) (2026)
- [NLLG Quarterly arXiv Report 09/24: What are the most influential current AI Papers?](https://mlsanity.com/paper/2412.12121/) (2024)
- [Optimizing Long-Form Clinical Text Generation with Claim-Based Rewards](https://mlsanity.com/paper/2510.02338/) (2025)
- [A Framework for Longitudinal Health AI Agents](https://mlsanity.com/paper/2604.12019/) (2026)
- [Are LLMs reliable? An exploration of the reliability of large language models in clinical note generation](https://mlsanity.com/paper/2505.17095/) (2025)
- [Enhancing Clinical Note Generation with ICD-10, Clinical Ontology Knowledge Graphs, and Chain-of-Thought Prompting Using GPT-4](https://mlsanity.com/paper/2512.05256/) (2025)
- [GuidelineGuard: An Agentic Framework for Medical Note Evaluation with Guideline Adherence](https://mlsanity.com/paper/2411.06264/) (2024)
- [Towards Scalable SOAP Note Generation: A Weakly Supervised Multimodal Framework](https://mlsanity.com/paper/2506.10328/) (2025)
- [DENSE: Longitudinal Progress Note Generation with Temporal Modeling of Heterogeneous Clinical Notes Across Hospital Visits](https://mlsanity.com/paper/2507.14079/) (2025)
- [Skin-SOAP: A Weakly Supervised Framework for Generating Structured SOAP Notes](https://mlsanity.com/paper/2508.05019/) (2025)
- [Which LLM to pick? Online Active Model Selection for Large Language Models](https://mlsanity.com/paper/2610.01592/) (2026)

## Abstract (arXiv)

Comprehensive clinical documentation is crucial for effective healthcare delivery, yet it poses a significant burden on healthcare professionals, leading to burnout, increased medical errors, and compromised patient safety. This paper explores the potential of generative AI (Artificial Intelligence) to streamline the clinical documentation process, specifically focusing on generating SOAP (Subjective, Objective, Assessment, Plan) and BIRP (Behavior, Intervention, Response, Plan) notes. We present a case study demonstrating the application of natural language processing (NLP) and automatic speech recognition (ASR) technologies to transcribe patient-clinician interactions, coupled with advanced prompting techniques to generate draft clinical notes using large language models (LLMs). The study highlights the benefits of this approach, including time savings, improved documentation quality, and enhanced patient-centered care. Additionally, we discuss ethical considerations, such as maintaining patient confidentiality and addressing model biases, underscoring the need for responsible deployment of generative AI in healthcare settings. The findings suggest that generative AI has the potential to revolutionize clinical documentation practices, alleviating administrative burdens and enabling healthcare professionals to focus more on direct patient care.