scholarly journals Digiprescription: An Intelligent System to Enable Paperless Prescription using Mobile Computing and Natural-language Processing

2020 ◽  
Author(s):  
Richard Zhang ◽  
Mary Zhao ◽  
Yucheng Jiang ◽  
Sophadeth Rithya ◽  
Yu Sun
Keyword(s):  
Natural Language Processing ◽  
Side Effects ◽  
Natural Language ◽  
Mobile Computing ◽  
Language Processing ◽  
Intelligent System ◽  
Drug Information ◽  
The Elderly ◽  
Black Box ◽  
Patient’S Information

Through our app, it is aimed to teach and tell the patients how to use the drug properly taking off the chances of putting their lives in danger, especially the elderly. It is also efficient to give patients these instructions as well as saving lots of paper. Because of the law, every drug that is given from the pharmacy to the user includes a receipt that lists information of, patient’s information, drug information, insurance information, directions on taking the medicine (black box warning issued by FDA), medication details on how it works, side effects, storage rules, and etc. These pieces of information are crucial to patients, where it tells them how to use the drug properly, but most people would throw these receipts away, which is a risk as well as a waste. Through using this app, the patient can efficiently get information on how to properly use the drug. This application is also helpful, where the user can choose to set reminders on when to eat this drug each week or month.

scholarly journals VNLP: Visible natural language processing

2021 ◽  
pp. 147387162110388
Author(s):  
Mohammad Alharbi ◽  
Matthew Roach ◽  
Tom Cheesman ◽  
Robert S Laramee
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Black Box ◽  
User Preferences ◽  
Text Similarity ◽  
Input Text ◽  
Visually Based ◽  
Pipeline Design

In general, Natural Language Processing (NLP) algorithms exhibit black-box behavior. Users input text and output are provided with no explanation of how the results are obtained. In order to increase understanding and trust, users value transparent processing which may explain derived results and enable understanding of the underlying routines. Many approaches take an opaque approach by default when designing NLP tools and do not incorporate a means to steer and manipulate the intermediate NLP steps. We present an interactive, customizable, visual framework that enables users to observe and participate in the NLP pipeline processes, explicitly manipulate the parameters of each step, and explore the result visually based on user preferences. The visible NLP (VNLP) pipeline design is then applied to a text similarity application to demonstrate the utility and advantages of a visible and transparent NLP pipeline in supporting users to understand and justify both the process and results. We also report feedback on our framework from a modern languages expert.

scholarly journals Resume Parser with Natural Language Processing

2021 ◽  
Author(s):  
Pornphat Sroison ◽  
Jonathan H. Chan
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Human Resource ◽  
Language Processing ◽  
Intelligent System ◽  
Job Description ◽  
Text Format ◽  
New Employees ◽  
Human Resource Department ◽  
Online Recruiting

<div>Because the online recruiting system has progressed, a large number of resumes were submitted. As a consequence, hiring new employees and reviewing a large number of resumes is a challenge for the human resource department or employer. Therefore, this system has helped employers by using an automated intelligent system based on natural language processing. This system can convert various formats of resumes to text format and can extract some important information. It is also possible to compare the applicant's resume and the job description to see the percentage of similarity as well. This system can assist the human resource department or employer in screening resumes before conducting interviews and finding the best candidate for the job position.</div>

scholarly journals Natural language processing of radiology reports to investigate the effects of the COVID-19 pandemic on the incidence and age distribution of fractures

2021 ◽  
Author(s):  
Florian Jungmann ◽  
B. Kämpgen ◽  
F. Hahn ◽  
D. Wagner ◽  
P. Mildenberger ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Age Distribution ◽  
The Elderly ◽  
Use Case ◽  
Fracture Detection ◽  
Root Cause ◽  
Radiology Reports ◽  
Number Of Patients

Abstract Objective During the COVID-19 pandemic, the number of patients presenting in hospitals because of emergency conditions decreased. Radiology is thus confronted with the effects of the pandemic. The aim of this study was to use natural language processing (NLP) to automatically analyze the number and distribution of fractures during the pandemic and in the 5 years before the pandemic. Materials and methods We used a pre-trained commercially available NLP engine to automatically categorize 5397 radiological reports of radiographs (hand/wrist, elbow, shoulder, ankle, knee, pelvis/hip) within a 6-week period from March to April in 2015–2020 into “fracture affirmed” or “fracture not affirmed.” The NLP engine achieved an F1 score of 0.81 compared to human annotators. Results In 2020, we found a significant decrease of fractures in general (p < 0.001); the average number of fractures in 2015–2019 was 295, whereas it was 233 in 2020. In children and adolescents (p < 0.001), and in adults up to 65 years (p = 0.006), significantly fewer fractures were reported in 2020. The number of fractures in the elderly did not change (p = 0.15). The number of hand/wrist fractures (p < 0.001) and fractures of the elbow (p < 0.001) was significantly lower in 2020 compared with the average in the years 2015–2019. Conclusion NLP can be used to identify relevant changes in the number of pathologies as shown here for the use case fracture detection. This may trigger root cause analysis and enable automated real-time monitoring in radiology.

scholarly journals Resume Parser with Natural Language Processing

2021 ◽  
Author(s):  
Pornphat Sroison ◽  
Jonathan H. Chan
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Human Resource ◽  
Language Processing ◽  
Intelligent System ◽  
Job Description ◽  
Text Format ◽  
New Employees ◽  
Human Resource Department ◽  
Online Recruiting

<div>Because the online recruiting system has progressed, a large number of resumes were submitted. As a consequence, hiring new employees and reviewing a large number of resumes is a challenge for the human resource department or employer. Therefore, this system has helped employers by using an automated intelligent system based on natural language processing. This system can convert various formats of resumes to text format and can extract some important information. It is also possible to compare the applicant's resume and the job description to see the percentage of similarity as well. This system can assist the human resource department or employer in screening resumes before conducting interviews and finding the best candidate for the job position.</div>

scholarly journals Natural Language Processing utilization in Healthcare

2019 ◽  
Vol 8 (6S2) ◽  
pp. 1117-1120
Keyword(s):  
Natural Language Processing ◽  
Side Effects ◽  
Natural Language ◽  
Language Processing ◽  
Clinical Results ◽  
Clinical Informatics ◽  
The Other ◽  
Psychological Wellness ◽  
The Individual ◽  
Assessment Strategies

The significance of consolidating Natural Language Processing (NLP) techniques in clinical informatics research has been progressively perceived over the previous years, and has prompted transformative advances. Ordinarily, clinical NLP frameworks are created and assessed on word, sentence, or record level explanations that model explicit traits and highlights, for example, archive content (e.g., persistent status, or report type), record segment types (e.g., current meds, past restorative history, or release synopsis), named substances and ideas (e.g., analyses, side effects, or medicines) or semantic qualities (e.g., nullification, seriousness, or fleetingness). While some NLP undertakings consider expectations at the individual or gathering client level, these assignments still establish a minority. Here we give an expansive synopsis and layout of the difficult issues engaged with characterizing suitable natural and outward assessment strategies for NLP look into that will be utilized for clinical results research, and the other way around. A specific spotlight is set on psychological wellness investigate, a zone still generally understudied by the clinical NLP look into network, however where NLP techniques are of prominent importance. Ongoing advances in clinical NLP strategy improvement have been huge, yet we propose more accentuation should be put on thorough assessment for the field to progress further. To empower this, we give noteworthy recommendations, including an insignificant convention that could be utilized when announcing clinical NLP strategy improvement and its assessment.

scholarly journals Natural Language Processing Empowered Mobile Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-2
Author(s):  
Tianyong Hao ◽  
Raymond Wong ◽  
Zhe He ◽  
Haoran Xie ◽  
Tak-Lam Wong ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Mobile Computing ◽  
Language Processing

Deliberative Democracy in an Unequal World: AText-As-DataStudy of South India’s Village Assemblies

2019 ◽  
Vol 113 (3) ◽  
pp. 623-640 ◽  
Author(s):  
RAMYA PARTHASARATHY ◽  
VIJAYENDRA RAO ◽  
NETHRA PALANISWAMY
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Deliberative Democracy ◽  
Language Processing ◽  
Real World ◽  
Local Development ◽  
Black Box ◽  
Rural India ◽  
Processing Methods ◽  
Indian Context

This paper opens the “black box” of real-world deliberation by usingtext-as-datamethods on a corpus of transcripts from the constitutionally mandatedgram sabhas, or village assemblies, of rural India. Drawing on normative theories of deliberation, we identify empirical standards for “good” deliberation based on one’s ability both to speak and to be heard, and use natural language processing methods to generate these measures. We first show that, even in the rural Indian context, these assemblies are not mere “talking shops,” but rather provide opportunities for citizens to challenge their elected officials, demand transparency, and provide information about local development needs. Second, we find that women are at a disadvantage relative to men; they are less likely to speak, set the agenda, and receive a relevant response from state officials. And finally, we show that quotas for women for village presidencies improve the likelihood that female citizens are heard.

scholarly journals A Bibliometric Review of Natural Language Processing Empowered Mobile Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Xieling Chen ◽  
Ruoyao Ding ◽  
Kai Xu ◽  
Shan Wang ◽  
Tianyong Hao ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Mobile Computing ◽  
Language Processing ◽  
Latent Dirichlet Allocation ◽  
Development Trend ◽  
Research Field ◽  
Statistical Characteristics ◽  
Future Research ◽  
Mobile Environment

Natural Language Processing (NLP) empowered mobile computing is the use of NLP techniques in the context of mobile environment. Research in this field has drawn much attention given the continually increasing number of publications in the last five years. This study presents the status and development trend of the research field through an objective, systematic, and comprehensive review of relevant publications available from Web of Science. Analysis techniques including a descriptive statistics method, a geographic visualization method, a social network analysis method, a latent dirichlet allocation method, and an affinity propagation clustering method are used. We quantitatively analyze the publications in terms of statistical characteristics, geographical distribution, cooperation relationship, and topic discovery and distribution. This systematic analysis of the field illustrates the publications evolution over time and identifies current research interests and potential directions for future research. Our work can potentially assist researchers in keeping abreast of the research status. It can also help monitoring new scientific and technological development in the research field.

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