Search Results - Large Language Models in coding

Enhanced BioGPT for Automated ICD-10 Medical Coding: Harnessing Domain-Tuned Large Language Models for Smarter Medical Coding

Authors: Ramadan, Medhat Hassan Mohamed Mohamed Naranjo-Zolotov, Mijail Juanovich RUN

Contributors: Ramadan, Medhat Hassan Mohamed Mohamed Naranjo-Zolotov, Mijail Juanovich RUN

Subject Terms: ICD-10 Classification, Clinical NLP, BioGPT, Large Language Models, MIMIC-IV, Hierarchical Attention, AI in Healthcare, Transformer Models, Health Informatics, SDG 3 - Good health and well-being, SDG 9 - Industry, innovation and infrastructure, SDG 17 - Partnerships for the goals, Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação

File Description: application/pdf

Availability: http://hdl.handle.net/10362/190738

Updating 'The Future of Coding': Qualitative Coding with Generative Large Language Models

Authors: Nga Than Leanne Fan Tina Law et al.

Source: Sociological Methods & Research. 2025 54(3):849-888.

Peer Reviewed: Y

Page Count: 40

Descriptors: Artificial Intelligence, Coding, Qualitative Research, Cues, Open Source Technology, Accuracy, Natural Language Processing, Social Science Research

Artificial Intelligence in Surgical Coding: Evaluating Large Language Models for Current Procedural Terminology Accuracy in Hand Surgery

Authors: Emily L. Isch Jamie Lee D. Mitchell Self et al.

Source: J Hand Surg Glob
Journal of Hand Surgery Global Online, Vol 7, Iss 2, Pp 181-185 (2025)

Subject Terms: AI in surgery, Current Procedural Terminology, ChatGPT, RD1-811, CPT coding, Hand surgery efficiency, Surgery, Large language models, Original Research

Access URL: https://pubmed.ncbi.nlm.nih.gov/40182863
https://doaj.org/article/8d30623353694bcca091b42486058c8d

Should we still teach or learn coding? A postgraduate student perspective on the use of large language models for coding in ecology and evolution

Authors: Heather Campbell Thomas Bluck Ella Curry et al.

Source: Methods in Ecology and Evolution, Vol 15, Iss 10, Pp 1767-1770 (2024)

Subject Terms: coding, education, ChatGPT, Ecology, Evolution, QH359-425, large language models, artificial intelligence, teaching, QH540-549.5

Access URL: https://doaj.org/article/f550b7ecc0f0498d9e1dd93e49668ab9

Evaluating Coding Proficiency of Large Language Models: An Investigation Through Machine Learning Problems

Authors: Eunbi Ko Pilsung Kang

Source: IEEE Access, Vol 13, Pp 52925-52938 (2025)

Subject Terms: Artificial intelligence, machine learning, large language model (LLM), generative pre-trained transformer (GPT), code generation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Access URL: https://doaj.org/article/3da42bc5636e4cee8125115edb69d7d2

Large Language Model in Medical Informatics: Direct Classification and Enhanced Text Representations for Automatic ICD Coding: Direct Classification and Enhanced Text Representations for Automatic ICD Coding

Authors: Boukhers, Zeyd Khan, Ameer Ali Ramadan, Qusai et al.

Source: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). :3066-3069

Subject Terms: Large Language Model, FOS: Computer and information sciences, Computer Science - Machine Learning, Clinical Text Analysis, LLAMA architecture, MultiResCNN, ICD Code Classification, Information Retrieval (cs.IR), Computer Science - Information Retrieval, Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2411.06823

VeriLeaky: Navigating IP Protection vs Utility in Fine-Tuning for LLM-Driven Verilog Coding

Authors: Wang, Zeng Shao, Minghao Nabeel, Mohammed et al.

Source: 2025 IEEE International Conference on LLM-Aided Design (ICLAD). :100-107

Subject Terms: Hardware Architecture, Machine Learning, FOS: Computer and information sciences, Cryptography and Security, Hardware Architecture (cs.AR), Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2503.13116

Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning

Authors: Puccioni, Laura Farshin, Alireza Scazzariello, Mariano et al.

Source: 2025 IEEE/ACM International Workshop on Large Language Models for Code (LLM4Code). :185-192

Subject Terms: I.2.2, D.1.2, Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Software Engineering, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, I.2.6, Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2501.05248

Beyond Functional Correctness: Investigating Coding Style Inconsistencies in Large Language Models

Authors: Yanlin Wang Tianyue Jiang Mingwei Liu et al.

Source: Proceedings of the ACM on Software Engineering. 2:690-712

Subject Terms: Software Engineering (cs.SE), FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Software Engineering

Access URL: http://arxiv.org/abs/2407.00456

Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning

Authors: Zhang, Xinlu Chen, Zhiyu Zoey Ye, Xi et al.

Source: Proceedings of the AAAI Conference on Artificial Intelligence. 39:25949-25957

Subject Terms: FOS: Computer and information sciences, Computer Science - Computation and Language, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computation and Language (cs.CL)

Access URL: http://arxiv.org/abs/2405.20535

VeriContaminated: Assessing LLM-Driven Verilog Coding for Data Contamination

Authors: Wang, Zeng Shao, Minghao Bhandari, Jitendra et al.

Source: 2025 IEEE International Conference on LLM-Aided Design (ICLAD). :117-123

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Cryptography and Security, Hardware Architecture (cs.AR), Computer Science - Hardware Architecture, Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2503.13572

Scaling hermeneutics: a guide to qualitative coding with LLMs for reflexive content analysis

Authors: Zackary Okun Dunivin

Source: EPJ Data Science, Vol 14, Iss 1, Pp 1-22 (2025)

Subject Terms: LLM, Computer applications to medicine. Medical informatics, R858-859.7, Text categorization, Content analysis, Qualitative coding, Digital humanities

Access URL: https://doaj.org/article/7f418cf589b34fd8a7af8c3485021c9e

Evaluating Large Language Model’s accuracy in current procedural terminology coding given operative note templates across various plastic surgery sub-specialties

Authors: Mia J. Carrarini Hilary Y. Liu Catherine K. Perez et al.

Source: Journal of Plastic, Reconstructive & Aesthetic Surgery. 106:50-52

Access URL: https://pubmed.ncbi.nlm.nih.gov/40367652

Towards Sustainable AI: Evaluating Efficiency of LLMs for Coding of Diagnoses from Veterinary Health Records

Authors: David Kott Adam Kiehl Connor Price et al.

Source: 2025 IEEE Swiss Conference on Data Science (SDS). :48-54

INTEGRATING LARGE LANGUAGE MODEL AND PSYCHOMETRIC ANALYSIS TO UNDERSTAND LEARNER'S CODING BEHAVIORS

Authors: Mo Zhang Chen Li Hongwen Guo et al.

Source: EDULEARN Proceedings. 1:9700-9707

Generative AI and Inter-rater Reliability: LLM Consistency in Coding Orders of Worth in Digital Political Debates

Authors: Ana Ioan Daniel Rosner Alexandru Radovici

Source: 2025 25th International Conference on Control Systems and Computer Science (CSCS). :633-640

Enhancing Developer Productivity: Benchmarking LLM-Powered Tools like GitHub Copilot and TabNine in Real-Time Coding Environments

Authors: Faten Slama Daniel Lemire

Source: 2025 IEEE 11th International Conference on Intelligent Data and Security (IDS). :39-45

Spicing Up LLMs: The Role of PAPRICA Pruning in Linear Computation Coding

Authors: Johanna S. Fröhlich Hans Rosenberger Ralf R. Müller

Source: 2025 IEEE Conference on Artificial Intelligence (CAI). :352-357

How Effective are LLMs for Data Science Coding? A Controlled Experiment

Authors: Nathalia Nascimento Everton Guimaraes Sai Sanjna Chintakunta et al.

Source: 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR). :211-222

Accessible and Reliable AI Coding Tutors: Augmenting Large Language Models with Retrieval-Augmented Generation for Java Programming

Authors: Guiu Puigcercos i Vilar Parvez Rashid Navid Hashemi Tonekaboni

Source: 2025 IEEE Global Engineering Education Conference (EDUCON). :1-10