Intelligent system and human factor caused medical errors

Sagi, Andor; Sabo, Anita; Kuljic, Bojan; Szakall, Tibor

doi:10.1109/sisy.2013.6662579

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Therefore, most research has focused on the system expectations of a normal and correct procedure to detect a lapse-based error, which includes errors made by medical doctors, pilots, and astronauts. Moreover, over 60% of errors result from human error [29,30].…”

Section: Unintentional-based Human Errormentioning

confidence: 99%

Micro-Behavioral Accidental Click Detection System for Preventing Slip-Based Human Error

Almehmadi¹

2021

Sensors

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Accidentally clicking on a link is a type of human error known as a slip in which a user unintentionally performs an unintended task. The risk magnitude is the probability of occurrences of such error with a possible substantial effect to which even experienced individuals are susceptible. Phishing attacks take advantage of slip-based human error by attacking psychological aspects of the users that lead to unintentionally clicking on phishing links. Such actions may lead to installing tracking software, downloading malware or viruses, or stealing private, sensitive information, to list a few. Therefore, a system is needed that detects whether a click on a link is intentional or unintentional and, if unintentional, can then prevent it. This paper proposes a micro-behavioral accidental click detection system (ACDS) to prevent slip-based human error. A within-subject-based experiment was conducted with 20 participants to test the potential of the proposed system. The results reveal the statistical significance between the two cases of intentional vs. unintentional clicks using a smartphone. Random tree, random forest, and support vector machine classifiers were used, exhibiting 82.6%, 87.2%, and 91.6% accuracy in detecting unintentional clicks, respectively.

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Section: Unintentional-based Human Errormentioning

confidence: 99%

Micro-Behavioral Accidental Click Detection System for Preventing Slip-Based Human Error

Almehmadi¹

2021

Sensors

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“…In this paper, we give the method of using boosting decision tree to analyze the medical data. The design method and the process of establishing boosting decision tree are described [2].…”

Section: Introductionmentioning

confidence: 99%

The Research on the Boosting Decision Tree Algorithm for Intelligent Medical System

Zou

2014

AMM

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Intelligent Medical Systems currently has been used in most advanced hospitals worldwide, and most of theses systems have the function module of guiding-patient-diagnosis, which makes the patient use this feature to get a preliminary treatment opinion based on their patients condition. In this paper, the way of enhancing the effect of guiding-patient-diagnosis with boosting decision tree algorithm is researched, and the paper describes the specific applying process of the algorithm. Finally, boosting decision tree algorithm prove to improve the efficiency of intelligent guiding function, making intelligent guiding diagnosis function accurate and reliable, which save the health care resources and the time of doctors and patients.

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Development and Evaluation of an IoT-Driven Auto-Infusion System with Advanced Monitoring and Alarm Functionalities

Kok,

Teo,

Koh

et al. 2024

2024 IEEE International Symposium on Circuits and Systems (ISCAS)

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Intelligent system and human factor caused medical errors

Cited by 3 publications

References 2 publications

Micro-Behavioral Accidental Click Detection System for Preventing Slip-Based Human Error

Micro-Behavioral Accidental Click Detection System for Preventing Slip-Based Human Error

The Research on the Boosting Decision Tree Algorithm for Intelligent Medical System

Development and Evaluation of an IoT-Driven Auto-Infusion System with Advanced Monitoring and Alarm Functionalities

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