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Do we do what they say we do? coding errors in urology

BJU INTERNATIONAL 2000年第4期85卷 389-391页

作者： Ballaro, A Oliver, S Emberton, M Inst Urol & Nephrol London W1P 7PN England

Objective To determine the accuracy of routine data coding in a large multispeciality urological unit. Materials and methods From the clinical records, the diagnosis and procedure codes were ascribed to 106 finished consultant episodes (FCEs) in urology, by two urological trainees. The codes were compared with those ascribed by professional hospital coders land of which the trainees were unaware) from information written on the audit form by junior medical staff. Where there were discrepancies in codes an error was recorded and the stage in the coding process in which it occurred was determined. Results Forty-eight coding errors were found in 38 of the 106 (36%) FCEs;34 (71%) were caused by inaccurate coding and 14 (29%) were the result of the incorrect completion of audit forms, Conclusion The clinical codes generated from the authors' department do not accurately reflect the clinical practice. If coding errors of this magnitude are typical of urology units in general, the concept of hospital performance tables (which will be generated using routine clinical data) is untenable unless data recording is given higher priority.

关键词： coding errors data-recording performance tables

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Rule-Based Detective Model for Medical CPT coding errors in an Outpatient Community Health Medical Center

Rule-Based Detective Model for Medical CPT Coding Errors in ...

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IISE Annual Conference and Expo 2024

作者： Lekham, Laith Abu Cooper, Tammy Hey, Ellen Wang, Yong Khasawneh, Mohammad T. Finger Lakes Community Health New York United States State University of New York Binghamton United States

ISBN: (纸本)9781713877851

Medical coding has been in place for years in the healthcare industry and constantly evolving. errors in medical coding can happen for multiple reasons such as improper understanding of medical coding guidelines, the complexity of the coding systems, and continuous changes in medical coding. This paper develops a rule-based model that detects certain CPT medical coding errors in an outpatient rural setting. The Python-based model can detect three types of predefined errors: under-coding, over-coding, and mismatched code. Each error type contained several scenarios of mistakes. The model was evaluated by medical coding experts using three datasets for validation (1,922 visits), testing (2,132 visits), and implementation (2,031 visits). The model identified 80 percent of the errors flagged by the experts during their review. Mismatched codes are the most common errors and 90% of these errors the model identified were corroborated by the expert panel. The model performance is consistent as the detection accuracy is highly similar for each error scenario using the three evaluation datasets. Based on the results, the model can effectively reduce the labor time and cost needed for manual audits by medical coders, generate more revenue, reduce costs of miscoded visits and claims, and improve coding practices and accuracy. The expected annual monetary benefit of the model at FLCH ranges from $70,000 to $100,000. One of the strengths of this model is its generalizability where it can be implemented at any outpatient medical center, as medical coding is standardized and universal. © IISE Annual Conference and Expo *** rights reserved.

关键词： coding errors

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Assessments of Channel coding Performance in Data Compression and Source coding 5th

Assessments of Channel Coding Performance in Data Compressio...

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Savita Bargavi, Manju Panwar, Rahul Shyam, Gopal Krishna Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

Channel coding is a technique used to boom the performance and reliability of records transmission. It is able to be used for facts compression and source coding, that are the procedures of reducing the amount of records that desires to be despatched across a *** of channel coding performance can be performed with the aid of analyzing the performance of the records compression and source coding techniques. This can be executed thru diverse measures, such as compression ratio, supply coding charge, mistakes detection and correction, and bit blunders rate. With the intention to appropriately verify the performance of the channel coding approach, all of these measures must be considered. The aim of channel coding is to reap the highest viable fee of data compression with minimal errors detection and correction, and bit blunders rates as little as possible. This guarantees that the records is transmitted securely and efficaciously. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： coding errors

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Noise-Agnostic Multitask Whisper Training for Reducing False Alarm errors in Call-for-Help Detection

arXiv

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arXiv 2025年

作者： Ryu, Myeonghoon Kim, June-Woo Oh, Minseok Lee, Suji Park, Han Deeply Inc. Seoul Korea Republic of Department of Artificial Intelligence Kyungpook National University Daegu Korea Republic of RSC LAB MODULABS Seoul Korea Republic of

Keyword spotting is often implemented by keyword classifier to the encoder in acoustic models, enabling the classification of predefined or open vocabulary keywords. Although keyword spotting is a crucial task in various applications and can be extended to call-for-help detection in emergencies, however, the previous method often suffers from scalability limitations due to retraining required to introduce new keywords or adapt to changing contexts. We explore a simple yet effective approach that leverages off-the-shelf pretrained ASR models to address these challenges, especially in call-for-help detection scenarios. Furthermore, we observed a substantial increase in false alarms when deploying call-for-help detection system in real-world scenarios due to noise introduced by microphones or different environments. To address this, we propose a novel noise-agnostic multitask learning approach that integrates a noise classification head into the ASR encoder. Our method enhances the model’s robustness to noisy environments, leading to a significant reduction in false alarms and improved overall call-for-help performance. Despite the added complexity of multitask learning, our approach is computationally efficient and provides a promising solution for call-for-help detection in real-world scenarios. © 2025, CC BY.

关键词： coding errors

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coding Scheme for Noisy Nanopore Sequencing with Backtracking and Skipping errors

Coding Scheme for Noisy Nanopore Sequencing with Backtrackin...

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IEEE International Symposium on Information Theory (ISIT)

作者： Chee, Yeow Meng Immink, Kees A. Schouhamer Vu, Van Khu Natl Univ Singapore Dept Ind Syst Engn & Management Singapore Singapore Turing Machines Inc NL-3016 DK Rotterdam Netherlands

ISBN: (纸本)9798350382853;9798350382846

In DNA-based data storage, sequencing the stored DNA is essential in reading the stored data. Nanopore sequencing, an emerging sequencing technology, has attracted a lot of attention recently owing to their various advantages, in particular, it is portable, scalable, automated and rapid. However, several kinds of errors, including inter-symbol interference, noisy measurement, backtracking, and skipping, reduce the accuracy of the technology. Several coding schemes have been proposed recently to deal with various kinds of error sources, especially inter-symbol interference and noisy measurement. In this work, we focus on backtracking and skipping errors and aim to design a good coding scheme to combat these errors. We first note that backtracking and skipping errors can be modelled as synchronization errors, including duplication and deletion errors. Next, we propose new families of codes to locate and correct all synchronization errors caused by backtracking and skipping. The proposed codes are constrained codes avoiding prescribed set of patterns. Then, we focus on studying these constrained codes. In particular, we present a method to compute their maximal asymptotic rates. For illustration, we use experimental data available online to compute the numerical results for maximal asymptotic rates of these codes.

关键词： coding errors

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Decimation of encoding errors in an optimum SNS folding ADC

Decimation of encoding errors in an optimum SNS folding ADC

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1995 IEEE International Symposium on Circuits and Systems (ISCAS-1995)

作者： PACE, PE SCHAFER, JL USN POSTGRAD SCHDEPT ELECT & COMP ENGNMONTEREYCA 93943

ISBN: (纸本)0780325702

The symmetrical number system (SNS) can be used as an efficient preprocessing technique to reduce the number of comparators in a folding ADC. This paper examines the issue of encoding errors that result when the separate channels m_i are brought back together to derive the input analog voltage. As an example, a unipolar 7-bit SNS ADC using pairwise relatively prime (PRP) moduli m_i= 4, m₂=5 and m₃=7 is evaluated numerically. Steady state transfer functions are shown which detail encoding errors that occur when the folded input samples lie at one of the code transition points. To discard the encoding errors that occur, a decimation band is constructed at each transition point. The effectiveness of the decimation band in eliminating the encoding errors is also quantified.

关键词： coding errors

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Class of codes correcting absorptions and emissions

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Physical Review A 2025年第2期111卷 022415-022415页

作者： Arda Aydin Alexander Barg ISR and Department of ECE University of Maryland College Park Maryland 20742 USA QuICS NIST University of Maryland College Park Maryland 20742 USA

We construct a general family of quantum codes that protect against all emission, absorption, dephasing, and raising or lowering errors up to an arbitrary fixed order. Such codes are known in the literature as absorption-emission (AE) codes. We derive simplified error correction conditions for a general AE code and show that any permutation-invariant code that corrects t or fewer errors can be mapped to an AE code that corrects up to order-t transitions. Carefully tuning the parameters of permutationally invariant codes, we construct several examples of efficient AE codes, hosted in systems with low total angular momentum. Our results also imply that spin codes can be mapped to AE codes, enabling us to characterize logical operators for certain subclasses of such codes.

关键词： coding errors

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On the Second-Order Achievabilities of Indirect Quadratic Lossy Source coding

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Yang, Huiyuan Yuan, Xiaojun University of Electronic Science and Technology of China National Key Laboratory on Wireless Communications Chengdu611731 China

This paper studies the second-order achievabilities of indirect quadratic lossy source coding for a specific class of source models, where the term "quadratic"denotes that the reconstruction fidelity of the hidden source is quantified by a squared error distortion measure. Specifically, it is assumed that the hidden source S can be expressed as S=(X)+W, where X is the observable source with alphabet X, () is a deterministic function, and W is a random variable independent of X, satisfying E[W]=0, E[W2]>0, E[W3]=0, and E[W6] © 2015 IEEE.

关键词： coding errors

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Just-In-Time Detection of Outdated Comments in Software Development by Jointly Reasoning

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IEEE Transactions on Consumer Electronics 2025年

作者： Tan, Jiaxi Guo, Shikai Tao, Zijian Yang, Zhiguo Li, Hui Dalian Maritime University School of Information Science and Technology Dalian China Key Laboratory of Artificial Intelligence of Dalian Dalian China Missouri State University College of Business SpringfieldMO United States

Code comments are a crucial source of software to learn various aspects of code. However, with the iterative upgrades of software, outdated code comments are increasingly prevalent. Inconsistencies in code comments can mislead developers and lead to potential errors. Due to the complexity of semantic information and interactions between source code and comments, previous studies have difficulty capturing the long-term and non-sequential dependencies in source code and the complex interaction information between code and comments. To address these challenges in outdated comment detection, we propose an approach named OutComDeter consists of the following four components, i.e., the data processing component, the jointly reasoning component, the feature extraction component and the outdated comment detection component. Firstly, the data processing component transforms source code and comments into edit sequences and comment sequences. Subsequently, to address the limitations of existing methods in capturing the interactive information between code and comments, the joint reasoning component employs two encoders with co-matching attention network to incorporate the joint relational information between code and comments into their respective feature representations. This joint relational information thereby contributes to the detection of outdated code comments. Furthermore, to mitigate the interference caused by the lack of long-term and non-sequential dependencies in source code for the task of outdated code comment detection, the feature extraction component leverages multi-head attention layers and dot-product attention layers to capture these dependencies, forming the final feature representations for both code and comments. Finally, the outdated comment detection will detect the outdated comments through a non-linear transformation. The experimental results indicate that OutComDeter outperforms the state-of-the-art methods in detecting outdated comments, as evidenc

关键词： coding errors

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How to leverage large language models for automatic ICD coding

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Computers in Biology and Medicine 2025年 189卷 109971-109971页

作者： Yoo, Youngju Kim, Sewon KAIST Yuseong-gu Daejeon Korea Republic of NAVER Digital Healthcare Lab Seongnam-si Gyeonggi-do Korea Republic of NAVER Cloud Seongnam-si Gyeonggi-do Korea Republic of

ICD coding, which involves assigning appropriate ICD codes to clinical notes, is essential for healthcare tasks such as health expense claims, insurance claims, and disease research. Manual ICD coding is time-consuming and prone to errors, increasing the need for automation. However, clinical notes often contain non-grammatical expressions, abbreviations, professional terms, and synonyms, making them notably noisy compared to general documents. Additionally, ICD coding faces challenges such as a broad label space and the long-tail problem, making automatic ICD coding highly challenging. Large Language Models (LLMs) have shown great potential in code extraction tasks due to their exceptional natural language understanding and information extraction capabilities. However, the unique characteristics of clinical records and ICD codes necessitate fine-tuning LLMs for optimal performance in ICD coding. In this study, we propose a novel fine-tuning framework for LLMs aimed at automatic ICD coding. Our framework introduces additional elements, including a label attention mechanism, note-relevant knowledge injection based on medical expressions, and knowledge-driven sampling to address the input token limitations of LLMs. Experiments on the MIMIC-III-50 dataset show that our framework outperforms vanilla fine-tuning in both micro and macro accuracy and F1 scores, with particularly significant improvements observed in encoder–decoder models. © 2025 Elsevier Ltd

关键词： coding errors

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