Radiologists and Their Noise: Variability in Human Judgment, Fallibility, and Strategies to Improve Accuracy

Radiology ◽  
2022 ◽  
Author(s):  
Diego Jaramillo
Keyword(s):  
Human Judgment ◽  
Improve Accuracy

Haunted by a Doppelgänger

2014 ◽  
Vol 61 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Bettina von Helversen ◽  
Stefan M. Herzog ◽  
Jörg Rieskamp
Keyword(s):  
Relevant Information ◽  
Psychological Research ◽  
Decision Makers ◽  
Human Judgment ◽  
Rule Based ◽  
New Employees ◽  
High Performing ◽  
Facial Similarity ◽  
Similarity Effect ◽  
Judgment Strategy

Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

Applications of computer technology to problems of human judgment and interpersonal conflict

1971 ◽  
Author(s):  
David A. Summers ◽  
Thomas R. Stewart ◽  
Peter J. R. Boyle ◽  
Monroe J. Miller ◽  
Kenneth R. Hammond
Keyword(s):  
Computer Technology ◽  
Interpersonal Conflict ◽  
Human Judgment

Use of Intraoperative Navigation Update to Improve Accuracy during Skull Base Surgery

2019 ◽  
Author(s):  
Holly Oemke ◽  
Margaret Pain ◽  
Daniel Charytonowicz ◽  
Leslie Schlachter ◽  
Anthony Costa ◽  
...  
Keyword(s):  
Skull Base ◽  
Skull Base Surgery ◽  
Intraoperative Navigation ◽  
Improve Accuracy

Use of Second Harmonic and Thermal Effects of Laser Voltage Probing for Better Fault Isolation

2016 ◽  
Author(s):  
Ramya Yeluri ◽  
Ravishankar Thirugnanasambandam ◽  
Cameron Wagner ◽  
Jonathan Urtecho ◽  
Jan M. Neirynck
Keyword(s):  
Duty Cycle ◽  
Thermal Effects ◽  
Second Harmonic ◽  
Fault Isolation ◽  
Advanced Technology ◽  
Temperature Dependent ◽  
First Case ◽  
Improve Accuracy ◽  
Degradation Monitoring ◽  
Technology Nodes

Abstract Laser voltage probing (LVP) has been extensively used for fault isolation over the last decade; however fault isolation in practice primarily relies on good-to-bad comparisons. In the case of complex logic failures at advanced technology nodes, understanding the components of the measured data can improve accuracy and speed of fault isolation. This work demonstrates the use of second harmonic and thermal effects of LVP to improve fault isolation with specific examples. In the first case, second harmonic frequency is used to identify duty cycle degradation. Monitoring the relative amplitude of the second harmonic helps identify minute deviations in the duty cycle with a scan over a region, as opposed to collecting multiple high resolution waveforms at each node. This can be used to identify timing degradation such as signal slope variation as well. In the second example, identifying abnormal data at the failing device as temperature dependent effect helps refine the fault isolation further.

scholarly journals Fast 10-Point DFT Algorithm for Power System Harmonic Analysis

2021 ◽  
Vol 11 (15) ◽  
pp. 7007
Author(s):  
Janusz P. Paplinski ◽  
Aleksandr Cariow
Keyword(s):  
Computational Complexity ◽  
Power System ◽  
Harmonic Analysis ◽  
Efficient Algorithm ◽  
System Analysis ◽  
Spectral Leakage ◽  
Power System Analysis ◽  
Improve Accuracy ◽  
The Cost ◽  
Harmonic Power

This article presents an efficient algorithm for computing a 10-point DFT. The proposed algorithm reduces the number of multiplications at the cost of a slight increase in the number of additions in comparison with the known algorithms. Using a 10-point DFT for harmonic power system analysis can improve accuracy and reduce errors caused by spectral leakage. This paper compares the computational complexity for an L×10M-point DFT with a 2M-point DFT.

scholarly journals “I can’t skip it”: does free report improve accuracy in false memories?

Memory ◽  
2021 ◽  
pp. 1-9
Author(s):  
Marina C. Wimmer ◽  
Ben Whalley ◽  
Timothy J. Hollins
Keyword(s):  
False Memories ◽  
Improve Accuracy

scholarly journals Humans rely more on algorithms than social influence as a task becomes more difficult

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Bogert ◽  
Aaron Schecter ◽  
Richard T. Watson
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Social Influence ◽  
Correct Answer ◽  
Online Reviews ◽  
Personal Networks ◽  
Human Judgment ◽  
Individual Decision ◽  
Individual Decision Making

AbstractAlgorithms have begun to encroach on tasks traditionally reserved for human judgment and are increasingly capable of performing well in novel, difficult tasks. At the same time, social influence, through social media, online reviews, or personal networks, is one of the most potent forces affecting individual decision-making. In three preregistered online experiments, we found that people rely more on algorithmic advice relative to social influence as tasks become more difficult. All three experiments focused on an intellective task with a correct answer and found that subjects relied more on algorithmic advice as difficulty increased. This effect persisted even after controlling for the quality of the advice, the numeracy and accuracy of the subjects, and whether subjects were exposed to only one source of advice, or both sources. Subjects also tended to more strongly disregard inaccurate advice labeled as algorithmic compared to equally inaccurate advice labeled as coming from a crowd of peers.

A LAMSTAR Network-Based Human Judgment Analysis

2017 ◽  
Vol 47 (6) ◽  
pp. 951-957 ◽  
Author(s):  
Jae M. Yoon ◽  
David He ◽  
Matthew L. Bolton
Keyword(s):  
Human Judgment ◽  
Judgment Analysis
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