Paper Citation Record · LEDGER

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

As of 20 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2501.05479.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.05479 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:48:15.298430Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:51:05.003185Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-16T10:51:05.837089Z

Reference resolution

47 of 47 outbound references displayed

verified exact5
verified fuzzy25
unresolved17
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 227a7dfb-def8-4114-8713-9a4c058cb0c6 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.168812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4368ff83-7056-4454-ae60-851364d4c772 · outbound

This paper cites Large language models in medicine.

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

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.153191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 12fe2896-6c5a-4f9a-bb32-810d13647bd1 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.137700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 33168f0e-e676-4597-8a41-cade40136453 · outbound

This paper cites ChatGPT: the future of discharge summaries? The Lancet Digital Health 2023;5(3):e107–8.

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

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.093949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac84db13-1068-426a-8e7a-ca3ca304a6e9 · outbound

This paper cites Ethics of large language models in medicine and medical research.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.113471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation be112e49-07e8-4c9e-ae8d-84dea2d383e7 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.099409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a55a6d2c-27d8-49e2-b21a-904f39f6488e · outbound

This paper cites Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.085085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b707078c-80d7-40c5-bad2-06cfddd00e94 · outbound

This paper cites Key challenges for delivering clinical impact with artificial intelligence.

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

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.069446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7dc0ecac-d5e4-43e4-b8da-30535a6c7985 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.054534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3f62c0d6-768a-47d6-9605-581c7be36e23 · outbound

This paper cites Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models [Internet].

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

Resolution: verified exact; doi, observed 2026-08-10T21:48:15.352966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 827485fd-c628-4253-a733-10e82ae73a83 · outbound

This paper cites Large Language Models Are Poor Medical Coders — Benchmarking of Medical Code Querying.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.039639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 63a778dc-0447-44c7-b87c-ea65733bcd2a · outbound

This paper cites The shaky foundations of large language models and foundation models for electronic health records.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.024162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d69667ea-0cd7-470b-b99e-52db62ffe21a · outbound

This paper cites A large language model for electronic health records.

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

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:16.008109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8224633-fce2-4599-991b-779c30b5fe2c · outbound

This paper cites Health system-scale language models are all-purpose prediction engines.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.992583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b86a4a4-465f-4abb-a746-0414639a81c6 · outbound

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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Source-reported events for the cited work

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Observation d6828f84-11f2-48a8-aee5-feadd8ce91f6 · outbound

This paper cites Language Models are Few-Shot Learners [Internet].

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

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.977222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 10a2219e-86ae-44bd-bcac-71a0e839bc17 · outbound

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

Resolution: verified exact; raw_fallback, observed 2026-08-10T21:48:15.765841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 60be5e83-5fc6-4712-9b71-3d72ffe15680 · outbound

This paper cites BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.962440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6aa7a931-8abe-4a74-b3b3-eda391940f7d · outbound

This paper cites Retrieval augmentation of large language models for lay language generation.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.948144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9732d203-0c24-41af-a9d2-b3b1d655a8f0 · outbound

This paper cites Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.169866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9210e0d-bcb3-408a-8849-0992e6700c3c · outbound

This paper cites Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.174538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9adac30-2b07-4462-9eb5-2913c9055273 · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.179415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7649f9ff-5be3-46b7-99e4-9b4cdb786eaf · outbound

This paper cites Towards Medical Billing Automation: NLP for Outpatient Clinician Note Classification [Internet].

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

Resolution: verified exact; doi, observed 2026-08-10T21:48:15.336251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5813739f-7fd4-499f-ba36-40376b542893 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.188716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a95929c0-0d45-4003-8f00-03e22578a2ef · outbound

This paper cites Introducing Phi-3: Redefining what’s possible with SLMs [Internet].

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.933540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3c86ae21-cf77-458c-8ae3-84da486e3c93 · outbound

This paper cites Link and code: Fast indexing with graphs and compact regression codes.

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

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:48:15.571717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 25b6327b-7328-4865-af41-b16b614fa701 · outbound

This paper cites Billion-scale similarity search with GPUs.

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

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.202907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ce512b9-0720-45c3-a140-f2c9fc33c718 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

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

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.208056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b62f2f98-81bc-40ca-8f66-0dc910c960e5 · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

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

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.212822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db5371fa-8468-44da-b616-f65549aa5bf3 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.217307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e32f619c-6154-4f35-bd4f-448a2881b775 · outbound

This paper cites ZeRO: Memory Optimizations Toward Training Trillion Parameter Models.

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

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.222015Z

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Observation 24ae9a37-3de0-472f-ac5b-de0e4f945a3c · outbound

This paper cites ZeRO-Offload: Democratizing Billion-Scale Model Training.

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

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.226897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ef9ad6c-2754-4681-bc46-3eb659514fe6 · outbound

This paper cites ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning.

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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Source-reported events for the cited work

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Observation 67cc0b49-e108-46cf-abd8-8594f6ba3840 · outbound

This paper cites A Thorough Examination of Decoding Methods in the Era of LLMs.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.236284Z

Source-reported events for the cited work

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Observation 00479d15-7a70-4df7-be8a-ff4fa07b6b98 · outbound

This paper cites Diagnosis code assignment: models and evaluation metrics.

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

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.918293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 52e5384a-88da-4351-9806-c022a67e50a8 · outbound

This paper cites 3M Inside Angle.

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

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.903093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6c4f54c2-6ab8-4f8d-bcd0-663371072532 · outbound

This paper cites ROUGE: A Package for Automatic Evaluation of Summaries [Internet].

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

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.888460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e6911924-3abc-46d9-aeaa-9e490655be1f · outbound

This paper cites METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments [Internet].

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.872751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 87bafd3e-b83b-4e5c-9071-c547b74ffe14 · outbound

This paper cites Development, Deployment, and Implementation of a Machine Learning Surgical Case Length Prediction Model and Prospective Evaluation.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.855065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 282d26bf-b311-4162-8518-d9c6f99bd12b · outbound

This paper cites Automated clinical coding: what, why, and where we are? NPJ Digit Med 2022;5(1):159.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.839767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7d46323-235b-4d5c-bcea-dccca301c308 · outbound

This paper cites A systematic literature review of automated clinical coding and classification systems.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.824652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f3217b3c-c415-42a4-a557-d67756e69ce1 · outbound

This paper cites 3M Inside Angle.

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

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.809541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 47d2d64c-3514-4b24-b082-9c3e7df905d7 · outbound

This paper cites Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines.

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

Resolution: verified exact; local_arxiv, observed 2026-08-10T21:48:15.425796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 25f98660-5016-457f-8034-45fe026c380b · outbound

This paper cites Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.284164Z

Source-reported events for the cited work

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Observation 5bbcff7e-ec8d-43f5-944b-b27924d41e70 · outbound

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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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.288718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57344f02-e239-491a-b3fc-86c4ce2f09cb · outbound

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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

Resolution: unresolved; no resolver link, observed 2026-08-10T21:48:15.293661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5383540-d865-4334-bdad-77b20cb537d2 · outbound

This paper cites Journal of AHIMA.

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

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:48:15.795603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation e6b51d0d-c4c8-4913-b2d1-14d9dac433d4 · inbound

The Rise of Small Language Models in Healthcare: A Comprehensive Survey cites this paper.

The Rise of Small Language Models in Healthcare: A Comprehensive Survey Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding

Reference 154

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:51:05.841026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.