24 papers · ranked by Valyu relevance
Sweta Mahaju, Jeffrey C. Carver, Gary L. Bradshaw
Context: Software development is a human-centric activity and hence vulnerable to human error. Human errors are errors in the human thought process. To ensure software quality, it is important for practitioners to understand how to manage these human errors. Organizations often introduce changes into the requirements…
Christina M. Lewis, Robert S. Gutzwiller
Previous work on indices of error-monitoring strongly supports that errors are distracting and can deplete attentional resources. In this study, we use an ecologically valid multitasking paradigm to test post-error behavior. It was predicted that after failing an initial task, a subject re-presented with that task in…
Marzieh Abbassinia, Omid Kalatpour, Majid Motamedzade, Alireza Soltanian + 1 more
'Alireza Soltanian' 'Iraj Mohammadfam'] Background: Human error is one of the major causes of accidents in the petrochemical industry. Under critical situation, human error is affected by complex factors. Managing such a situation is important to prevent losses and injury. This study aimed to develop a dynamic model of…
Anna Poranen, Anne Kouvonen, Hilla Nordquist
Background The dynamic and challenging work environment of the prehospital emergency care settings creates many challenges for paramedics. Previous studies have examined adverse events and patient safety activities, but studies focusing on paramedics’ perspectives of factors contributing to human error are lacking. In…
Shu-Huan Ko, Min-Chih Hsieh, Run-Feng Huang, Daniele Giansanti
Medical institutions worldwide strive to avoid adverse medical events, including adverse medication-related events. However, studies on the comprehensive analysis of medication-related adverse events are limited. Therefore, we aimed to identify the error factors contributing to medication-related adverse events using…
Joseph A. Cafazzo, Abigail J. Sellen, Don Norman
Objective To honor the legacy of John Senders, a distinguished member of the Human Factors and Ergonomics Society, by a short, personal history of him, but then to honor his legacy by extending it through our own professional opinions, with an emphasis on the study of human error and its implications for healthcare…
Rahul Pandey, Hemant Purohit, Carlos Castillo, Valerie L. Shalin
High-quality human annotations are necessary for creating effective machine learning-driven stream processing systems. We study hybrid stream processing systems based on a Human-In-The-Loop Machine Learning (HITL-ML) paradigm, in which one or many human annotators and an automatic classifier (trained at least partially…
Fakhradin Ghasemi, Mohammad Babamiri, Zahra Pashootan, Muhammad Junaid Farrukh
'Muhammad Junaid Farrukh'] Medication errors can endanger the health and safety of patients and need to be managed appropriately. This study aimed at developing a new and comprehensive method for estimating the probability of medication errors in hospitals. An extensive literature review was conducted to identify…
J.D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke + 2 more
'Nikhil Garg' 'Emma Pierson'] Algorithms provide powerful tools for detecting and dissecting human bias and error. Here, we develop machine learning methods to to analyze how humans err in a particular high-stakes task: image interpretation. We leverage a unique dataset of 16,135,392 human predictions of whether a…
Ray Panko
Research on spreadsheet errors is substantial, compelling, and unanimous. It has three simple conclusions. The first is that spreadsheet errors are rare on a per-cell basis, but in large programs, at least one incorrect bottom-line value is very likely to be present. The second is that errors are extremely difficult to…
Edna C. Cieslik, Markus Ullsperger, Martin Gell, Simon B. Eickhoff + 1 more
Brain mechanisms of error processing have often been investigated using response interference tasks and focusing on the posterior medial frontal cortex, which is also implicated in resolving response conflict in general. Thereby, the role other brain regions may play has remained undervalued. Here, activation…
Ashton Anderson, Jon Kleinberg, Sendhil Mullainathan
An increasing number of domains are providing us with detailed trace data on human decisions in settings where we can evaluate the quality of these decisions via an algorithm. Motivated by this development, an emerging line of work has begun to consider whether we can characterize and predict the kinds of decisions…
Hiroki Ohashi, Hiroto Nagayoshi
This study tackles on a new problem of estimating human-error potential on a shop floor on the basis of wearable sensors. Unlike existing studies that utilize biometric sensing technology to estimate people's internal state such as fatigue and mental stress, we attempt to estimate the human-error potential in a…
Hans Kirschner, Jana Tegelbeckers, Daniel Janko, Luisa Göde + 1 more
Sleep deprivation is known to impair cognitive performance, yet its effects on error awareness and subsequent behavioral adjustments remain incompletely understood. Here, we investigated how sleep loss affects the use of subjective performance evaluation to guide post-error adaptations. Thirty healthy adults completed…
Christopher D. Wallbridge, Erwin Jose Lopez Pulgarin
This position paper looks briefly at the way we attempt to program robotic AI systems. Many AI systems are based on the idea of trying to improve the performance of one individual system to beyond so-called human baselines. However, these systems often look at one shot and one-way decisions, whereas the real world is…
Naoyuki Okamoto, Michael Taylor, Takatomi Kubo, Shin Ishii + 2 more
Mistakes are valuable learning opportunities, yet in uncertain environments, whether a lack of reward is due to poor performance or bad luck can be hard to tell. To investigate how humans address this issue, we developed a visuomotor task where rewards depended on either skill or chance. Participants consistently…
Eva Niessen, Jonas Wickert, Martin Schober, Gereon R. Fink + 2 more
Influential theories on error processing assume that when we conduct errors adaptive processes are triggered to improve our behaviour and prevent errors in the future. These processes appear to be more effective after participants have detected an error. Therefore, the assessment of error awareness allowing a…
Gezelle Dali, Méadhbh Brosnan, Jeggan Tiego, Beth P. Johnson + 3 more
Goal-directed behaviour is dependent upon the ability to detect errors and implement appropriate post-error adjustments. Accordingly, several studies have explored the neural activity underlying error-monitoring processes, identifying the insula cortex as crucial for error awareness and reporting mixed findings with…
Authors not listed
Nuclear Magnetic Resonance (NMR) structure determination is an important problem in education, industry, and research. Solving NMR spectra requires expert knowledge, critical thinking, and careful evaluation of multiple features of spectral data. This study explores the capabilities of large language models (LLMs) for…
Tyler J Adkins, Han Zhang, Taraz G Lee
Humans tend to slow down after making an error. A longstanding account of this post-error slowing is that people are simply more cautious. However, accuracy typically does not improve following an error leading some researchers to suggest that an initial ‘orienting’ response may initially impair performance immediately…
Nancy C Elder, Harini Pallerla, Saundra Regan
Background Physicians are being asked to report errors from primary care, but little is known about how they apply the term "error." This study qualitatively assesses the relationship between the variety of error definitions found in the medical literature and physicians' assessments of whether an error occurred in a…
Authors not listed
A Python script for the systematic, high-throughput analysis of accurate mass data was developed and tested on over 3,000 Supporting Information (SI) PDFs from Organic Letters. For each SI file, quadruplets of molecular formula, measured ion, e.g. [M+Na]+, reported calculated and found masses were extracted and…
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Automation of experiments in cloud laboratories promises to revolutionize scientific research by enabling remote experimentation and improving reproducibility. However, maintaining quality control without constant human oversight remains a critical challenge. Here, we present a novel machine learning framework for…
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This study presents a validation and refinement of the “yellow cards” error detection workflow that can be applied to any property connected to molecular structure. In our implementation the workflow employed 5 predictive models with each assigning a “yellow card” to 5% of the entries with worst prediction accuracy.…