scholarly journals Development and implementation of an LIS-based validation system for autoverification toward zero defects in the automated reporting of laboratory test results

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Di Jin ◽  
Qing Wang ◽  
Dezhi Peng ◽  
Jiajia Wang ◽  
Bijuan Li ◽  
...  
Keyword(s):  
New Method ◽  
Effectiveness Evaluation ◽  
Test Results ◽  
Human Machine Interaction ◽  
Time Consumption ◽  
Laboratory Test Results ◽  
B Virus ◽  
Machine Interaction ◽  
Clinical Complaint ◽  
Manual Verification

Abstract Background Validation of the autoverification function is one of the critical steps to confirm its effectiveness before use. It is crucial to verify whether the programmed algorithm follows the expected logic and produces the expected results. This process has always relied on the assessment of human–machine consistency and is mostly a manually recorded and time-consuming activity with inherent subjectivity and arbitrariness that cannot guarantee a comprehensive, timely and continuous effectiveness evaluation of the autoverification function. To overcome these inherent limitations, we independently developed and implemented a laboratory information system (LIS)-based validation system for autoverification. Methods We developed a correctness verification and integrity validation method (hereinafter referred to as the "new method") in the form of a human–machine dialog. The system records personnel review steps and determines whether the human–machine review results are consistent. Laboratory personnel then analyze the reasons for any inconsistency according to system prompts, add to or modify rules, reverify, and finally improve the accuracy of autoverification. Results The validation system was successfully established and implemented. For a dataset consisting of 833 rules for 30 assays, 782 rules (93.87%) were successfully verified in the correctness verification phase, and 51 rules were deleted due to execution errors. In the integrity validation phase, 24 projects were easily verified, while the other 6 projects still required the additional rules or changes to the rule settings. Taking the Hepatitis B virus test as an example, from the setting of 65 rules to the automated releasing of 3000 reports, the validation time was reduced from 452 (manual verification) to 275 h (new method), a reduction in validation time of 177 h. Furthermore, 94.6% (168/182) of laboratory users believed the new method greatly reduced the workload, effectively controlled the report risk and felt satisfied. Since 2019, over 3.5 million reports have been automatically reviewed and issued without a single clinical complaint. Conclusion To the best of our knowledge, this is the first report to realize autoverification validation as a human–machine interaction. The new method effectively controls the risks of autoverification, shortens time consumption, and improves the efficiency of laboratory verification.

scholarly journals Development and Implementation of A LIS-Based Validation System for Autoverification Toward Zero Defects in The Automated Reporting of Laboratory Test Results

2021 ◽  
Author(s):  
Di Jin ◽  
Qing Wang ◽  
Dezhi Peng ◽  
Jiajia Wang ◽  
Yating Cheng ◽  
...  
Keyword(s):  
Information System ◽  
The Other ◽  
New Method ◽  
Effectiveness Evaluation ◽  
Laboratory Information System ◽  
Test Results ◽  
Time Consumption ◽  
Laboratory Test Results ◽  
Manual Recording ◽  
Clinical Complaint

Abstract BackgroundValidation of the autoverification function is the most critical step to confirm its effectiveness before use. It is crucial to verify whether the programmed algorithm follows the expected logic and produces the expected results. In recent years, this process has always been centered on the assessment of human-machine consistency and mostly takes the form of manual recording, which is a time-consuming activity with inherent subjectivity and arbitrariness, and cannot guarantee a comprehensive, timely and continuous effectiveness evaluation of the autoverification function. To overcome these inherent limitations, we independently developed and implemented a laboratory information system (LIS)-based validation system for autoverification.MethodsWe developed a correctness verification and integrity validation method (hereinafter referred to as the "new method") in the form of a human-machine dialogue. The system records the personnel’s review steps and determines if the human-machine review results are consistent. If they are inconsistent, the laboratory personnel analyze the reasons for the inconsistency according to the system prompts, add to or modify the rules, reverify, and finally improve the accuracy of autoverification.ResultsThe validation system was successfully established and implemented. For a dataset consisting of 833 rules for 30 assays, 782 rules (93.87%) were successfully verified in the correctness verification phase, and 51 rules were deleted due to execution errors. In the integrity validation phase, 24 projects were easily verified, while the other 6 projects still required the addition of new rules or changes to the rule settings. From setting the rules to the automated reportion, the time difference between manual validation and the new method, was statistically significant (χ2=11.06, p=0.0009), with the new method greatly reducing validation time. Since 2017, the new method has been used in 32 laboratories, and 15.8 million reports have been automatically reviewed and issued without a single clinical complaint.ConclusionTo the best of our knowledge, this is the first report to realize autoverification validation in the form of a human-machine interaction.The new method can effectively control the risks of autoverification, shorten time consumption, and improve the efficiency of laboratory verification.

scholarly journals The Profiles of Hepatitis B and C Virus Infections in Prison-Assisted Citizens

Biomedika ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 51-57
Author(s):  
Patricia Gita Naully
Keyword(s):  
Hepatitis B ◽  
Codes Of Ethics ◽  
Assay Method ◽  
Enzyme Linked Immunosorbent Assay ◽  
Correctional Institution ◽  
Test Results ◽  
Virus Infections ◽  
Injection Drugs ◽  
Laboratory Test Results ◽  
B Virus

Prison-assisted citizens or prisoners are one of the groups of people who are at high risk of Hepatitis B and C virus infections. The data on the prevalence of both viruses in prisoners in Indonesia are still limited. This study aims to determine the profiles of Hepatitis B and C virus infections in prison-assisted citizens in the Class IIA Narcotics Correctional Institution in Bandung Regency. A total of 30 prisoners were used as the samples in this study. All procedures performed in this study were following the applicable codes of ethics. The presence of surface antigens of Hepatitis B virus (HBsAg) in serums was detected using a qualitative sandwich Enzyme-Linked Immunosorbent Assay method. The existence of antibodies of the Hepatitis C virus (Anti-VHC) was detected using the immunochromatography method. The laboratory test results have shown five people (16.7%) were positive on the HBsAg test and one person (3.3%) was positive on the anti-VHC test. One case of Hepatitis B and C co-infection was also found in the prison-assisted citizens who were in the Class IIA Narcotics Correctional Institution in Bandung Regency. All the prisoners infected by the Hepatitis B and C viruses used injection drugs, had tattoos on their bodies and never received vaccinations.

scholarly journals Rates of HIV and Hepatitis Infections in Clients Entering Heroin-Assisted Treatment between 2003 and 2013 and Risk Factors for Hepatitis C Infection

2015 ◽  
Vol 22 (4) ◽  
pp. 181-191 ◽  
Author(s):  
Maria Dickson-Spillmann ◽  
Severin Haug ◽  
Ambros Uchtenhagen ◽  
Philip Bruggmann ◽  
Michael P. Schaub
Keyword(s):  
Hepatitis C ◽  
Hepatitis A Virus ◽  
Multiple Logistic Regression Analysis ◽  
Female Gender ◽  
Test Results ◽  
Hepatitis C Infection ◽  
Heroin Users ◽  
Laboratory Test Results ◽  
B Virus ◽  
Immunodeficiency Virus

Background/Aims: We report on the rates of hepatitis A virus (HAV), hepatitis B virus (HBV), hepatitis C virus (HCV) and human immunodeficiency virus (HIV) in 1,313 clients entering heroin-assisted treatment (HAT) in Switzerland from 2003 to 2013. We identify predictors of HCV infection. Methods: Data were collected using questionnaires within 2 weeks of clients' first entry into HAT. Prevalence of HAV, HBV, HCV and HIV was calculated using laboratory test results collected at entry or using reports of older test results. Predictors of HCV status were identified through multiple logistic regression analysis. Results: Results show stable rates of HIV-positive clients and decreasing proportions of HAV- and HBV-infected clients. In 2013, there were 12% (n = 8) HIV-, 20% (n = 12) HAV-, 20% (n = 12) HBV- and 52% HCV- (n = 34) positive clients. Vaccination against HAV and HBV had become more frequent. Predictors of positive HCV status included older age, female gender, earlier year of entry, having spent 1 month or more in detention or prison, use of injected heroin and more years of intravenous use. Conclusion: Our results highlight the fact that efforts to prevent and test for infections and to promote vaccination against HAV and HBV in heroin users need to be continued.

scholarly journals Backstepping Control of Open-Chain Linkages Actuated by Antagonistic Hill Muscles

2020 ◽  
Vol 142 (10) ◽  
Author(s):  
Holly Warner ◽  
Hanz Richter ◽  
Antonie J. van den Bogert
Keyword(s):  
Inverse Dynamics ◽  
Human Subjects ◽  
Kinematic Chain ◽  
Test Results ◽  
Robotic Rehabilitation ◽  
Healthcare Applications ◽  
Human Machine Interaction ◽  
Open Chain ◽  
Prosthetic Devices ◽  
Machine Interaction

Abstract For human–machine interaction, the forward progression of technology, particularly controls, regularly brings about new possibilities. Indeed, healthcare applications have flourished in recent years, including robotic rehabilitation, exercise, and prosthetic devices. Testing these devices with human subjects is inherently risky and frequently inconsistent. This work offers a novel simulation framework toward overcoming many of these difficulties. Specifically, generating a closed-loop dynamic model of a human or a human subsystem that can connect to device simulations allows simulated human–machine interaction. In this work, a muscle-actuated open kinematic chain linkage is generated to simulate the human, and a backstepping controller based on inverse dynamics is derived. The control architecture directly addresses muscle redundancy, and two options to resolve this redundancy are evaluated. The specific case of a muscle-actuated arm linkage is developed to illustrate the framework. Trajectory tracking is achieved in simulation. The muscles recruited to meet the tracking goal are in agreement with the method used to solve the redundancy problem. In the future coupling such simulations to any relevant simulation of a machine will provide safe, insightful preprototype test results.

Effect of Ibuprofen on Serum Laboratory Test Results

1983 ◽  
Vol 40 (6) ◽  
pp. 1025-1034
Author(s):  
Carol L. Colvin ◽  
Raymond J. Townsend ◽  
William R. Gillespie ◽  
Kenneth S. Albert
Keyword(s):  
Laboratory Test ◽  
Test Results ◽  
Laboratory Test Results

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

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