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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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Computation of the Optimal Error Exponent Function for Fixed-Length Lossy Source coding in Discrete Memoryless Sources

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IEEE Transactions on Information Theory 2025年第5期71卷 3360-3372页

作者： Jitsumatsu, Yutaka Kyushu University Department of Informatics Fukuoka819-0395 Japan

Marton’s optimal error exponent for the lossy source coding problem is defined as a non-convex optimization problem. This fact had prevented us to develop an efficient algorithm to compute it. This problem is caused by the fact that the rate-distortion function R(Δ |P) is potentially non-concave in the probability distribution P for a fixed distortion level Δ . The main contribution of this paper is the development of a parametric expression that is in perfect agreement with the inverse function of the Marton exponent. This representation has two layers. The inner layer is convex optimization and can be computed efficiently. The outer layer, on the other hand, is a non-convex optimization with respect to two parameters. We give a method for computing the Marton exponent based on this representation. © 1963-2012 IEEE.

关键词： coding errors

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Asymptotically Optimal Codes for (t, s)-Burst Error

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IEEE Transactions on Information Theory 2025年第3期71卷 1570-1584页

作者： Sun, Yubo Lu, Ziyang Zhang, Yiwei Ge, Gennian Capital Normal University School of Mathematical Sciences Beijing100048 China Shandong University Key Laboratory of Cryptologic Technology and Information Security Ministry of Education The School of Cyber Science and Technology Shandong Qingdao266237 China

Recently, codes for correcting a burst of errors have attracted significant attention. One of the most important reasons is that bursts of errors occur in certain emerging techniques, such as DNA storage. In this paper, we investigate a type of error, called a (t,s) -burst, which deletes t consecutive symbols and inserts s arbitrary symbols at the same coordinate. Note that a (t,s) -burst error can be seen as a generalization of a burst of insertions (t=0), a burst of deletions (s=0), and a burst of substitutions (t=s). Our main contribution is to give explicit constructions of q-ary (t,s)-burst correcting codes with log n + O(1) bits of redundancy for any given constant non-negative integers t, s, and q ≥ 2. These codes have optimal redundancy up to an additive constant. Furthermore, we apply our (t,s)-burst correcting codes to combat other various types of errors and improve the corresponding results. In particular, one of our byproducts is a permutation code capable of correcting a burst of t stable deletions with log n + O(1) bits of redundancy, which is optimal up to an additive constant. © 1963-2012 IEEE.

关键词： coding errors

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LLMER: Crafting Interactive Extended Reality Worlds with JSON Data Generated by Large Language Models

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IEEE Transactions on Visualization and Computer Graphics 2025年第5期31卷 2715-2724页

作者： Chen, Jiangong Wu, Xiaoyi Lan, Tian Li, Bin Pennsylvania State University Department of Electrical Engineering United States George Washington University Department of Electrical and Computer Engineering United States

The integration of Large Language Models (LLMs) like GPT-4 with Extended Reality (XR) technologies offers the potential to build truly immersive XR environments that interact with human users through natural language, e.g., generating and animating 3D scenes from audio inputs. However, the complexity of XR environments makes it difficult to accurately extract relevant contextual data and scene/object parameters from an overwhelming volume of XR artifacts. It leads to not only increased costs with pay-per-use models, but also elevated levels of generation errors. Moreover, existing approaches focusing on coding script generation are often prone to generation errors, resulting in flawed or invalid scripts, application crashes, and ultimately a degraded user experience. To overcome these challenges, we introduce LLMER, a novel framework that creates interactive XR worlds using JSON data generated by LLMs. Unlike prior approaches focusing on coding script generation, LLMER translates natural language inputs into JSON data, significantly reducing the likelihood of application crashes and processing latency. It employs a multi-stage strategy to supply only the essential contextual information adapted to the user's request and features multiple modules designed for various XR tasks. Our preliminary user study reveals the effectiveness of the proposed system, with over 80% reduction in consumed tokens and around 60% reduction in task completion time compared to state-of-the-art approaches. The analysis of users' feedback also illuminates a series of directions for further optimization. © 1995-2012 IEEE.

关键词： coding errors

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Byzantine-Resilient Gradient coding through Local Gradient Computations

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IEEE Transactions on Information Theory 2025年第4期71卷 3142-3156页

作者： Hofmeister, Christoph Massny, Luis Yaakobi, Eitan Bitar, Rawad Information and Technology at the Technical University of Munich School of Computation Germany CS Department of Technion Israel Institute of Technology Israel

We consider gradient coding in the presence of an adversary controlling so-called malicious workers trying to corrupt the computations. Previous works propose the use of MDS codes to treat the responses from malicious workers as errors and correct them using the error-correction properties of the code. This comes at the expense of increasing the replication, i.e., the number of workers each partial gradient is computed by. In this work, we propose a way to reduce the replication to s+1 instead of 2s + 1 in the presence of s malicious workers. Our method detects erroneous inputs from the malicious workers, transforming them into erasures. This comes at the expense of s additional local computations at the main node and additional rounds of light communication between the main node and the workers. We define a general framework and give fundamental limits for fractional repetition data allocations. Our scheme is optimal in terms of replication and local computation and incurs a communication cost that is asymptotically, in the size of the dataset, a multiplicative factor away from the derived bound. We furthermore show how additional redundancy can be exploited to reduce the number of local computations and communication cost, or, alternatively, tolerate straggling workers. © 1963-2012 IEEE.

关键词： coding errors

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Combinatorial alphabet-dependent bounds for insdel codes

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IEEE Transactions on Information Theory 2025年第5期71卷 3544-3559页

作者： Kong, Xiangliang Tamo, Itzhak Wei, Hengjia Tel Aviv University Department of Electrical Engineering-Systems Tel Aviv-Yafo6997801 Israel Xi'an Jiaotong University School of Mathematics and Statistics Xi'an710049 China

Error-correcting codes resilient to synchronization errors such as insertions and deletions are known as insdel codes. In this paper, we present several new combinatorial upper and lower bounds on the maximum size of q-ary insdel codes. Our main upper bound is a spherepacking bound obtained by solving a linear programming (LP) problem. It improves upon previous results for cases when the distance d or the alphabet size q is large. Our first lower bound is derived from a connection between insdel codes and matchings in special hypergraphs. This lower bound, together with our upper bound, shows that for fixed block length n and edit distance d, when q is sufficiently large, the maximum size of insdel codes is qn-d/2 + 1/(dn/2 - 1)(1 ± o(1)). The second lower bound refines Alon et al.'s recent logarithmic improvement on Levenshtein's GV-type bound and extends its applicability to large q and d. © 1963-2012 IEEE.

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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