Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding | Paper Citation Record

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This paper cites A study of generative large language model for medical research and healthcare.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding A study of generative large language model for medical research and healthcare

Reference 1

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Large language models in medicine

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This paper cites Using ChatGPT to write patient clinic letters.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Using ChatGPT to write patient clinic letters

Reference 3

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding ChatGPT: the future of discharge summaries? The Lancet Digital Health 2023;5(3):e107–8

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Ethics of large language models in medicine and medical research

Reference 5

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This paper cites Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine

Reference 6

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios

Reference 7

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Key challenges for delivering clinical impact with artificial intelligence

Reference 8

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This paper cites GPT versus Resident Physicians — A Benchmark Based on Official Board Scores.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding GPT versus Resident Physicians — A Benchmark Based on Official Board Scores

Reference 9

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models [Internet]

Reference 10

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Large Language Models Are Poor Medical Coders — Benchmarking of Medical Code Querying

Reference 11

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding The shaky foundations of large language models and foundation models for electronic health records

Reference 12

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding A large language model for electronic health records

Reference 13

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Health system-scale language models are all-purpose prediction engines

Reference 14

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This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 15

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Language Models are Few-Shot Learners [Internet]

Reference 16

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This paper cites Potential for GPT Technology to Optimize Future Clinical Decision-Making Using Retrieval-Augmented Generation.

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Potential for GPT Technology to Optimize Future Clinical Decision-Making Using Retrieval-Augmented Generation

Reference 17

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials

Reference 18

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Retrieval augmentation of large language models for lay language generation

Reference 19

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

Reference 20

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning

Reference 21

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Lost in the Middle: How Language Models Use Long Contexts

Reference 22

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Towards Medical Billing Automation: NLP for Outpatient Clinician Note Classification [Internet]

Reference 23

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 24

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Introducing Phi-3: Redefining what’s possible with SLMs [Internet]

Reference 25

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Link and code: Fast indexing with graphs and compact regression codes

Reference 26

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Billion-scale similarity search with GPUs

Reference 27

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 28

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding QLoRA: Efficient Finetuning of Quantized LLMs

Reference 29

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 30

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Reference 31

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding ZeRO-Offload: Democratizing Billion-Scale Model Training

Reference 32

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning

Reference 33

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding A Thorough Examination of Decoding Methods in the Era of LLMs

Reference 34

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Diagnosis code assignment: models and evaluation metrics

Reference 35

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding 3M Inside Angle

Reference 36

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding ROUGE: A Package for Automatic Evaluation of Summaries [Internet]

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments [Internet]

Reference 38

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Development, Deployment, and Implementation of a Machine Learning Surgical Case Length Prediction Model and Prospective Evaluation

Reference 39

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Automated clinical coding: what, why, and where we are? NPJ Digit Med 2022;5(1):159

Reference 40

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding A systematic literature review of automated clinical coding and classification systems

Reference 41

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding 3M Inside Angle

Reference 42

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines

Reference 43

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning

Reference 44

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 45

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 46

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Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding Journal of AHIMA

Reference 47

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