scholarly journals First study of the RuPatient health information system with optical character recognition of medical records based on machine learning

2022 ◽  
Vol 20 (8) ◽  
pp. 3080
Author(s):  
A. A. Komkov ◽  
V. P. Mazaev ◽  
S. V. Ryazanova ◽  
D. N. Samochatov ◽  
E. V. Koshkina ◽  
...  
Keyword(s):  
Information System ◽  
Health Information ◽  
Medical Records ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Health Information System ◽  
Document Management ◽  
Medical Documentation ◽  
Optical Character

RuPatient health information system (HIS) is a computer program consisting of a doctor-patient web user interface, which includes algorithms for recognizing medical record text and entering it into the corresponding fields of the system.Aim. To evaluate the effectiveness of RuPatient HIS in actual clinical practice.Material and methods. The study involved 10 cardiologists and intensivists of the department of cardiology and сardiovascular intensive care unit of the L. A. Vorokhobov City Clinical Hospital 67 We analyzed images (scanned copies, photos) of discharge reports from patients admitted to the relevant departments in 2021. The following fields of medical documentation was recognized: Name, Complaints, Anamnesis of life and illness, Examination, Recommendations. The correctness and accuracy of recognition of entered information were analyzed. We compared the recognition quality of RuPatient HIS and a popular optical character recognition application (FineReader for Mac).Results. The study included 77 pages of discharge reports of patients from various hospitals in Russia from 50 patients (men, 52%). The mean age of patients was 57,7±7,9 years. The number of reports with correctly recognized fields in various categories using the program algorithms was distributed as follows: Name — 14 (28%), Diagnosis — 13 (26%), Complaints — 40 (80%), Anamnesis — 14 (28%), Examination — 24 (48%), Recommendations — 46 (92%). Data that was not included in the category was also recognized and entered in the comments field. The number of recognized words was 549±174,9 vs 522,4±215,6 (p=0,5), critical errors in words — 2,1±1,6 vs 4,4±2,8 (p<0,001), non-critical errors — 10,3±4,3 vs 5,6±3,3 (p<0,001) for RuPatient HIS and optical character recognition application for a personal computer, respectively.Conclusion. The developed RuPatient HIS, which includes a module for recognizing medical records and entering data into the corresponding fields, significantly increases the document management efficiency with high quality of optical character recognition based on neural network technologies and the automation of filling process.

Kurzweil Reading Machine: A Partial Evaluation of Its Optical Character Recognition Error Rate

1979 ◽  
Vol 73 (10) ◽  
pp. 389-399
Author(s):  
Gregory L. Goodrich ◽  
Richard R. Bennett ◽  
William R. De L'aune ◽  
Harvey Lauer ◽  
Leonard Mowinski
Keyword(s):  
Error Rate ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Partial Evaluation ◽  
Error Rates ◽  
Recognition Error ◽  
Optical Character ◽  
Printed Materials ◽  
High Level

This study was designed to assess the Kurzweil Reading Machine's ability to read three different type styles produced by five different means. The results indicate that the Kurzweil Reading Machines tested have different error rates depending upon the means of producing the copy and upon the type style used; there was a significant interaction between copy method and type style. The interaction indicates that some type styles are better read when the copy is made by one means rather than another. Error rates varied between less than one percent and more than twenty percent. In general, the user will find that high quality printed materials will be read with a relatively high level of accuracy, but as the quality of the material decreases, the number of errors made by the machine also increases. As this error rate increases, the user will find it increasingly difficult to understand the spoken output.

scholarly journals Development of the documents comparison module for an electronic document management system

2019 ◽  
pp. 527-533
Author(s):  
M A Mikheev ◽  
P Y Yakimov
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Document Management ◽  
Electronic Document ◽  
Text Documents ◽  
Text Document ◽  
Document Management System ◽  
Optical Character ◽  
Electronic Document Management ◽  
Scanned Image

The article is devoted to solving the problem of document versions comparison in electronic document management systems. Systems-analogues were considered, the process of comparing text documents was studied. In order to recognize the text on the scanned image, the technology of optical character recognition and its implementation — Tesseract library were chosen. The Myers algorithm is applied to compare received texts. The software implementation of the text document comparison module was implemented using the solutions described above.

Quality of Routine Health Information System Data and Associated Factors Among Departments in Public Health Facilities of Harari Region, Ethiopia

2021 ◽  
Author(s):  
Adisu Tafari Shama ◽  
Hirbo Shore Roba ◽  
Admas Abera ◽  
Negga Baraki
Keyword(s):  
Public Health ◽  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Health Information System ◽  
Health Facilities ◽  
Quality Data ◽  
Public Health Facilities ◽  
System Data

Abstract Background: Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia.Methods: A cross-sectional study was conducted in all public health facilities in Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation check-lists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P-value <0.05. Result: The study found a good quality data in 51.35% (95% CI, 44.6-58.1) of the departments in public health facilities in Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to departments found in the health posts. The presence of trained staffs able to fill reporting formats (AOR=2.474; 95%CI: 1.124-5.445) and provision of feedback (AOR=3.083; 95%CI: 1.549-6.135) were also significantly associated with data quality. Conclusion: The level of good data quality in the public health facilities was less than the expected national level. Training should be provided to increase the knowledge and skills of the health workers.

scholarly journals Evaluasi Sistem Informasi Manajemen Puskesmas Guna Mendukung Penerapan Sikda Generik Menggunakan Metode Hot Fit Di Kabupaten Purworejo

2016 ◽  
Vol 4 (2) ◽  
pp. 129-138 ◽  
Author(s):  
Viera Juniver Thenu ◽  
Eko Sediyono ◽  
Cahya Tri Purnami
Keyword(s):  
Information System ◽  
Health Center ◽  
Health Information ◽  
Health Information System ◽  
Health Centers ◽  
Accurate Information ◽  
System Quality ◽  
District Health ◽  
Routine Monitoring

Purworejo District Health Office (DHO) has developed Health Center Management Information System (HCMIS) to provide quick, precise, and accurate information for supporting the process of decision making and the policy of services at Health Center. However, there was still any empty forms and did not use the system. To standardize Health Information System, Ministry of Health has released a concept of Generic SIKDA. Therefore, the system applied by Purworejo DHO needs to be evaluated using the method of HOT fit. This was qualitative research using indepth interview and direct observation. Main informants were nine data operators and informants for triangulation purpose was six persons from health centers and five persons from DHO. Furthermore, data were analyzed using content analysis. The result of this research revealed that the application of HCMIS at Purworejo DHO was equal to Generic SIKDA. The system had been applied routinely but there was no a guidance book and training. Number of human resources was sufficient. However, there needed to make an implementer team of Health Information System in accordance with competency. There was no routine monitoring and current budget was not sufficient to maintain hardware to support the system. Quality of the system used was good, easy to use, and available of menu to communicate data. Unfortunately, quality of resulted information had still been inaccurate and incomplete because it did not cover data of services at Subsidiary Health Centers (SHC) and Village Health Posts (VHP). The lateness of services was related to a funding procedure. HCMIS at Purworejo DHO was equal to Generic SIKDA but it had not been used to make a decision. As a suggestion, DHO needs to conduct training, monitor, and provide hardware and a network. Meanwhile, Health Centers needs to make a commitment for applying the HCMIS maximally by SHC and VHP.

scholarly journals Quality of the Mental Health Information System in a Specialized Mental Hospital in Bangladesh

2018 ◽  
Vol 26 (2) ◽  
pp. 180
Author(s):  
Nazmun Nuri ◽  
Malabika Sarker ◽  
Helal Ahmed ◽  
Mohammad Hossain ◽  
Fekri Dureab ◽  
...  
Keyword(s):  
Mental Health ◽  
Information System ◽  
Health Information ◽  
Mental Hospital ◽  
Health Information System ◽  
Mental Health Information ◽  
Mental Health Information System

scholarly journals About design medical databases and information systems for the organization and management of clinical processes

2020 ◽  
Vol 6 (2) ◽  
pp. 20-26
Author(s):  
Ahrorjon A. Abdumanonov ◽  
◽  
Ruslan E. Aliyev ◽  
Muhammajan K. Karabayev ◽  
Vokhidjon G. Hoshimov ◽  
...  
Keyword(s):  
Information System ◽  
Information Systems ◽  
Health Information ◽  
Medical Information ◽  
Health Information System ◽  
Information Provision ◽  
Document Management ◽  
Organization And Management ◽  
Other Information ◽  
Single Standard

In article questions of development of automated, integrated information systems and databases (DB), created by the authors to ensure that the information and intellectual support of organizations and management of clinical processes in a general hospital. Analyze the schema information and intellectual support for the main stages of activity of the doctor in the organization of clinical processes and proved the effectiveness of the transition to electronic document management and management of patient records. The techniques and steps in the process of designing a database of such systems. Presented data models based on relational principles and taking into account the peculiarities of information provision of medical care in a clinical hospital emergency medicine. Sanctified issues for creating a database implemented taking into account the specifics of health care regulations, standards and related problems of formalization and standardization of information, the problem of choice of database management systems (DBMS), including for medical applications, the issues of intellectualization of the database and the formation of a knowledge base. Showing crucial modeling domain – automation object articles in this case – the diagnostic and treatment process. The main requirements to the database integrated health information systems. Questions of formalization entered into the database of medical and other information, the solution of which the authors carried out through the creation of special electronic templates for all aspects of medical practice hospital. Being developed by leading medical specialists clinic, they do not only facilitate the design, but also remind us that we should find out, to ask to examine and help select the best tactics. This kind of technology is human-computer interaction – an element of the programming actions of the doctor. This option is the task of formalizing entered into the database of medical information used to provide a single standard of medical information, standardize the order of the information entered into the database. The results of the analysis of the effectiveness of the developed information system and performance of its database in the course of their use in the clinical setting. In particular, we studied the performance, response time and server load when working with different categories of users – doctors, nurses, administrators, and etc., which have shown the applicability of the developed health information system and its database to optimize the organization of clinical processes in the conditions of the experiment.

IMPROVEMENT OF THE COLOR TEXT IMAGE BINARIZATION METHOD USING THE MINIMUM-DISTANCE CLASSIFIER

2021 ◽  
Vol 4 (1) ◽  
pp. 57-70
Author(s):  
Marina V. Polyakova ◽  
Alexandr G. Nesteryuk
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Minimum Distance ◽  
Color Images ◽  
Connected Components ◽  
Image Binarization ◽  
Optical Character ◽  
Binarization Method ◽  
Text Images

Optical character recognition systems for the images are used to convert books and documents into electronic form, to automate accounting systems in business, when recognizing markers using augmented reality technologies and etс. The quality of optical character recognition, provided that binarization is applied, is largely determined by the quality of separation of the foreground pixels from the background. Methods of text image binarization are analyzed and insufficient quality of binarization is noted. As a way of research the minimum-distance classifier for the improvement of the existing method of binarization of color text images is used. To improve the quality of the binarization of color text images, it is advisable to divide image pixels into two classes, “Foreground” and “Background”, to use classification methods instead of heuristic threshold selection, namely, a minimum-distance classifier. To reduce the amount of processed information before applying the classifier, it is advisable to select blocks of pixels for subsequent processing. This was done by analyzing the connected components on the original image. An improved method of the color text image binarization with the use of analysis of connected components and minimum-distance classifier has been elaborated. The research of the elaborated method showed that it is better than existing binarization methods in terms of robustness of binarization, but worse in terms of the error of the determining the boundaries of objects. Among the recognition errors, the pixels of images from the class labeled “Foreground” were more often mistaken for the class labeled “Background”. The proposed method of binarization with the uniqueness of class prototypes is recommended to be used in problems of the processing of color images of the printed text, for which the error in determining the boundaries of characters as a result of binarization is compensated by the thickness of the letters. With a multiplicity of class prototypes, the proposed binarization method is recommended to be used in problems of processing color images of handwritten text, if high performance is not required. The improved binarization method has shown its efficiency in cases of slow changes in the color and illumination of the text and background, however, abrupt changes in color and illumination, as well as a textured background, do not allowing the binarization quality required for practical problems.

Effects of Ambient Light, Camcorder Settings, and Automated License Plate Reader Settings on Plate Transcription Rates

2002 ◽  
Vol 1804 (1) ◽  
pp. 56-61 ◽  
Author(s):  
Michael Plotnikov ◽  
Paul W. Shuldiner
Keyword(s):  
Character Recognition ◽  
Template Matching ◽  
Optical Character Recognition ◽  
License Plate ◽  
Ambient Light ◽  
Light Conditions ◽  
Video Images ◽  
Optical Character ◽  
Plate Reader

The ability of an automated license plate reading (ALPR) system to convert video images of license plates into computer records depends on many factors. Of these, two are readily controlled by the operator: the quality of the video images captured in the field and the internal settings of the ALPR used to transcribe these images. A third factor, the light conditions under which the license plate images are acquired, is less easily managed, especially when camcorders are used in the field under ambient light conditions. A set of experiments was conducted to test the effects of ambient light conditions, video camcorder adjustments, and internal ALPR settings on the percent of correct reads attained by a specific type of ALPR, one whose optical character recognition process is based on template matching. Images of rear license plates were collected under four ambient light conditions: overcast with no shadows, and full sunlight with the sun in front of the camcorder, behind the camcorder, and orthogonal to the line of sight. Three camcorder exposure settings were tested. Two of the settings made use of the camcorder’s internal light meter, and the third relied solely on operator judgment. The license plates read ranged from 41% to 72%, depending most strongly on ambient light conditions. In all cases, careful adjustment of the ALPR led to significantly improved read rates over those obtained by using the manufacturer’s recommended default settings. Exposure settings based on the operator’s judgment worked best in all instances.

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