scholarly journals PILOT PROJECT FOR ELECTRONIC REIMBURSEMENT SYSTEM FOR PHYSICIANS IN INDONESIA

2020 ◽  
Vol 1 (2) ◽  
pp. 37-43
Author(s):  
Taiyin Wu
Keyword(s):  
Domain Knowledge ◽  
Learning Algorithm ◽  
Pilot Project ◽  
Electronic System ◽  
User Friendliness ◽  
Time Saving ◽  
Electronic Form ◽  
User Friendly ◽  
Relationship Of ◽  
Sql Query

A healthcare department in remove community of Indonesia aimed for reducing paperwork and improving the electronic system. As part of a pilot project, one aspect was replaced from manual to the electronic format. The proposed system was use of electronic form for claiming for fee reimbursement made by the physicians. The design of the system is intranet based and consisted of two separate portals. The first portal is for physicians and second portal is for billing clerk. The interface is user-friendly and packed with pre-defined codes set in several of its fields and sub-fields. The electronic form is also linked to a centralized database from which a physician can copy the existing patients record. For improving the system variance from individual needs, decision support algorithm is used. Whereas, for improving the system performance, machine learning algorithm is used. For data query, database query was designed. The relationship of columns in the database is displayed as a tabulated form to the user. In situation where a user selects a particular column, a filtered display mechanism displays those columns which satisfying the portion of the query already constructed. For obtaining data from the tabulated database, the SQL query is adapted. Rule-based knowledge inference model is utilized for reasoning about terminology and required domain knowledge. The inference used is algorithmic and helpful in performing all necessary tasks under the suitable billing circumstances. A survey is conducted with 35 physicians for judging their perception towards the system. Results of the survey indicate that most participants find the system suitable and better than the paper-based system in terms of several dimensions such as user friendliness, time saving, reducing errors, and accuracy.

scholarly journals The Social Media and Language Use: The Case of Facebook

2019 ◽  
Vol 10 (4) ◽  
pp. 9
Author(s):  
Michael Alozie Nwala ◽  
Isaac Tamunobelema
Keyword(s):  
Social Media ◽  
Language Learning ◽  
Language Use ◽  
Writing Style ◽  
User Friendliness ◽  
Time Saving ◽  
The Social ◽  
Negative Implication ◽  
User Friendly ◽  
Great Danger

The social media is now the fastest and easiest means of communication; it is very popular and most of its sites are accessible. The Facebook, one of the popular types of the social media is not just common among youngsters; it is very dynamic, user-friendly and specific. This paper using the descriptive design and Technological Determision (TD) theory, investigates the language of the Facebook and discovers that the platform is awash with a lot of cyberslangs, acronyms, morphological shortenings, initialisms, contractions and neologisms. The paper discovers that the writing style of the Facebook departs from the known conventional ways of writing, a situation where a word can be represented in any form deemed fit by the user. Again, it is observed that the flexibility of the platform, its economic sensitivity or time saving nature and its user friendliness makes the platform attractive. But the negative implication of all these is that it is anti-pedagogy and portends great danger to language learning and usage.

scholarly journals Determining the impact of postoperative complications in neurosurgery based on simulated longitudinal smartphone app-based assessment

2021 ◽  
Author(s):  
Lion D. Comfort ◽  
Marian C. Neidert ◽  
Oliver Bozinov ◽  
Luca Regli ◽  
Martin N. Stienen
Keyword(s):  
Postoperative Complications ◽  
Feasibility Study ◽  
Well Being ◽  
Smartphone Application ◽  
Simulated Patients ◽  
Subjective Well Being ◽  
Longitudinal Assessment ◽  
User Friendliness ◽  
User Friendly ◽  
The Impact

Abstract Background Complications after neurosurgical operations can have severe impact on patient well-being, which is poorly reflected by current grading systems. The objective of this work was to develop and conduct a feasibility study of a new smartphone application that allows for the longitudinal assessment of postoperative well-being and complications. Methods We developed a smartphone application “Post OP Tracker” according to requirements from clinical experience and tested it on simulated patients. Participants received regular notifications through the app, inquiring them about their well-being and complications that had to be answered according to their assigned scenarios. After a 12-week period, subjects answered a questionnaire about the app’s functionality, user-friendliness, and acceptability. Results A total of 13 participants (mean age 34.8, range 24–68 years, 4 (30.8%) female) volunteered in this feasibility study. Most of them had a professional background in either health care or software development. All participants downloaded, installed, and applied the app for an average of 12.9 weeks. On a scale of 1 (worst) to 4 (best), the app was rated on average 3.6 in overall satisfaction and 3.8 in acceptance. The design achieved a somewhat favorable score of 3.1. One participant (7.7%) reported major technical issues. The gathered patient data can be used to graphically display the simulated outcome and assess the impact of postoperative complications. Conclusions This study suggests the feasibility to longitudinally gather postoperative data on subjective well-being through a smartphone application. Among potential patients, our application indicated to be functional, user-friendly, and well accepted. Using this app-based approach, further studies will enable us to classify postoperative complications according to their impact on the patient’s well-being.

The Red Legs RATED tool to improve diagnosis of lower limb cellulitis in the emergency department

2021 ◽  
Vol 30 (12) ◽  
pp. S22-S29
Author(s):  
Gillian O'Brien ◽  
Patricia White
Keyword(s):  
Emergency Department ◽  
Lower Limb ◽  
Treatment Guidelines ◽  
Positive Impact ◽  
Data Gathering ◽  
Pilot Project ◽  
Accurate Diagnosis ◽  
Evidence Based ◽  
Significant Burden ◽  
User Friendly

Background: Lower limb cellulitis poses a significant burden for the Irish healthcare system. Accurate diagnosis is difficult, with a lack of validated evidence-based tools and treatment guidelines, and difficulties distinguishing cellulitis from its imitators. It has been suggested that around 30% of suspected lower limb cellulitis is misdiagnosed. An audit of 132 patients between May 2017 and May 2018 identified a pattern of misdiagnosis in approximately 34% of this cohort. Objective: The aim of this pilot project was to develop a streamlined service for those presenting to the emergency department with red legs/suspected cellulitis, through introduction of the ‘Red Leg RATED’ tool for clinicians. Method: The tool was developed and introduced to emergency department clinicians. Individuals (n=24) presenting with suspected cellulitis over 4 weeks in 2018 were invited to participate in data gathering. Finally, clinician questionnaire feedback regarding the tool was evaluated. Results: Fourteen participants consented, 6 female and 8 male with mean age of 65 years. The tool identified 50% (n=7) as having cellulitis, of those 57% (n=4) required admission, 43% (n=3) were discharged. The remainder who did not have cellulitis (n=7) were discharged. Before introduction of the tool, all would typically have been admitted to hospital for further assessment and management of suspected lower limb cellulitis. Overall, 72% (n=10) of patients who initially presented with suspected cellulitis were discharged, suggesting positive impact of the tool. Clinician feedback suggested all were satisfied with the tool and contents. Conclusion: The Red Leg RATED tool is user friendly and impacts positively on diagnosis treatment and discharge. Further evaluation is warranted.

scholarly journals High-Throughput Analysis of Selected Urinary Hydroxy Polycyclic Aromatic Hydrocarbons by an Innovative Automated Solid-Phase Microextraction

Molecules ◽  
2018 ◽  
Vol 23 (8) ◽  
pp. 1869 ◽  
Author(s):  
Stefano Dugheri ◽  
Alessandro Bonari ◽  
Matteo Gentili ◽  
Giovanni Cappelli ◽  
Ilenia Pompilio ◽  
...  
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
High Throughput ◽  
Aromatic Hydrocarbons ◽  
High Throughput Screening ◽  
Solid Phase Microextraction ◽  
Solid Phase ◽  
User Friendliness ◽  
High Throughput Analysis ◽  
Polycyclic Aromatic ◽  
User Friendly

High-throughput screening of samples is the strategy of choice to detect occupational exposure biomarkers, yet it requires a user-friendly apparatus that gives relatively prompt results while ensuring high degrees of selectivity, precision, accuracy and automation, particularly in the preparation process. Miniaturization has attracted much attention in analytical chemistry and has driven solvent and sample savings as easier automation, the latter thanks to the introduction on the market of the three axis autosampler. In light of the above, this contribution describes a novel user-friendly solid-phase microextraction (SPME) off- and on-line platform coupled with gas chromatography and triple quadrupole-mass spectrometry to determine urinary metabolites of polycyclic aromatic hydrocarbons 1- and 2-hydroxy-naphthalene, 9-hydroxy-phenanthrene, 1-hydroxy-pyrene, 3- and 9-hydroxy-benzoantracene, and 3-hydroxy-benzo[a]pyrene. In this new procedure, chromatography’s sensitivity is combined with the user-friendliness of N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide on-fiber SPME derivatization using direct immersion sampling; moreover, specific isotope-labelled internal standards provide quantitative accuracy. The detection limits for the seven OH-PAHs ranged from 0.25 to 4.52 ng/L. Intra-(from 2.5 to 3.0%) and inter-session (from 2.4 to 3.9%) repeatability was also evaluated. This method serves to identify suitable risk-control strategies for occupational hygiene conservation programs.

scholarly journals An Agent-Based Approach to Interbank Market Lending Decisions and Risk Implications

2018 ◽  
Author(s):  
Anqi Liu ◽  
Cheuk Yin Jeffrey Mo ◽  
Mark E. Paddrik ◽  
Steve Y. Yang
Keyword(s):  
Learning Algorithm ◽  
Risk Preferences ◽  
Interbank Market ◽  
Agent Based ◽  
Market Structures ◽  
Key Characteristics ◽  
Interbank Lending ◽  
Lending Decisions ◽  
Relationship Of ◽  
The Relationship

In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literatur A key finding of this study is that risk preferences at individual bank level can lead to unique interbank market structures which are suggestive of the capacity that the market responds to surprising

Reporting a User Study on a Visual Editor to Compose Rules in Active Documents

2014 ◽  
pp. 182-203 ◽  
Author(s):  
Federico Cabitza ◽  
Iade Gesso
Keyword(s):  
Medical Record ◽  
User Study ◽  
End Users ◽  
Visual Language ◽  
Visual Languages ◽  
User Friendliness ◽  
Domain Specific ◽  
Specific Rule ◽  
User Friendly ◽  
It Skills

In the last years, researchers are exploring the feasibility of visual language editors in domain-specific domains where their alleged user-friendliness can be exploited to involve end-users in configuring their artifacts. In this chapter, the authors present an experimental user study conducted to validate the hypothesis that adopting a visual language could help prospective end-users of an electronic medical record define their own document-related local rules. This study allows them to claim that their visual rule editor based on the OpenBlocks framework can be used with no particular training as proficiently as with specific training, and it was found user-friendly by the user panel involved. Although the conclusions of this study cannot be broadly generalized, the findings are a preliminary contribution to show the importance of visual languages in domain-specific rule definition by end-users with no particular IT skills, like medical doctors are supposed to represent.

Library and Information Science Female Undergraduate Preference for Facebook as Information Sharing Tool

2021 ◽  
pp. 245-261
Author(s):  
Adeyinka Tella ◽  
Oluwole Olumide Durodolu ◽  
Stephen Osahon Uwaifo
Keyword(s):  
Information Sharing ◽  
Undergraduate Students ◽  
Social Engagement ◽  
Information Science ◽  
Library And Information Science ◽  
Female Undergraduate ◽  
User Friendliness ◽  
User Friendly ◽  
Correlated Factors ◽  
Survey Approach

This study has examined the library and information science female undergraduates' preference for Facebook as an information-sharing tool. A survey approach was adopted using a questionnaire to collect data from 457 LIS female undergraduate students drawn from five library schools in Nigeria. The findings of the study have demonstrated that most significant factors that lead to the use of Facebook for information sharing among LIS female undergraduate students are user-friendly nature of the tool, personal gain, enjoyment, and self-efficacy while the least factors are social engagement and empathy. User-friendliness nature of Facebook has the highest correlation with the preference for Facebook as an information-sharing tool by female students followed by enjoyment while learning and empathy are the least correlated factors.

A Post-Pandemic Strategy to Support Lifelong and Work-Integrated Learning

2022 ◽  
pp. 203-219
Author(s):  
Peter Mozelius
Keyword(s):  
Communities Of Practice ◽  
Lifelong Learning ◽  
Real World ◽  
Knowledge Society ◽  
Pilot Project ◽  
Insurance Companies ◽  
Integrated Learning ◽  
Pedagogical Aspect ◽  
Work Integrated Learning ◽  
User Friendly

Lifelong work-integrated learning is a key challenge in the growing knowledge society, with the Corona pandemic as a catalyst for technology enhancement. This chapter argues for the need of a post-pandemic strategy that rethinks not only the pedagogical aspect but also the technology enhanced and collaborative aspects of lifelong and work-integrated learning. The strategy that is presented in this chapter is based on the author's experience from the BUFFL initiative, a pilot project for industry development at banks and insurance companies through technology-enhanced lifelong learning. The recommendation is a strategy tailored for the target group that supports the work-integrated learning aim of academia providing useful theories for real-world tasks in the industry. Some important components in the strategy are 1) to extend pedagogy with andragogy and heutagogy, 2) the design of user-friendly hybrid environments, and 3) blended communities of practice.

scholarly journals A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

Science ◽  
2018 ◽  
Vol 362 (6419) ◽  
pp. 1140-1144 ◽  
Author(s):  
David Silver ◽  
Thomas Hubert ◽  
Julian Schrittwieser ◽  
Ioannis Antonoglou ◽  
Matthew Lai ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Reinforcement Learning ◽  
Domain Knowledge ◽  
Learning Algorithm ◽  
Search Techniques ◽  
Domain Specific ◽  
Evaluation Functions ◽  
History Of ◽  
World Champion ◽  
Reinforcement Learning Algorithm

The game of chess is the longest-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. By contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go by reinforcement learning from self-play. In this paper, we generalize this approach into a single AlphaZero algorithm that can achieve superhuman performance in many challenging games. Starting from random play and given no domain knowledge except the game rules, AlphaZero convincingly defeated a world champion program in the games of chess and shogi (Japanese chess), as well as Go.

Programming Language Support for Implementing Machine Learning Algorithms

2020 ◽  
pp. 402-421
Author(s):  
Anitha Elavarasi S. ◽  
Jayanthi J.
Keyword(s):  
Machine Learning ◽  
Programming Languages ◽  
Programming Language ◽  
Domain Knowledge ◽  
Learning Algorithm ◽  
Mathematical Optimization ◽  
Machine Learning Algorithms ◽  
Application Development ◽  
Machine Learning Applications ◽  
And Control

Machine learning provides the system to automatically learn without human intervention and improve their performance with the help of previous experience. It can access the data and use it for learning by itself. Even though many algorithms are developed to solve machine learning issues, it is difficult to handle all kinds of inputs data in-order to arrive at accurate decisions. The domain knowledge of statistical science, probability, logic, mathematical optimization, reinforcement learning, and control theory plays a major role in developing machine learning based algorithms. The key consideration in selecting a suitable programming language for implementing machine learning algorithm includes performance, concurrence, application development, learning curve. This chapter deals with few of the top programming languages used for developing machine learning applications. They are Python, R, and Java. Top three programming languages preferred by data scientist are (1) Python more than 57%, (2) R more than 31%, and (3) Java used by 17% of the data scientists.

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