VBSRL: A Semantic Frame-Based Approach for Data Extraction from Unstructured Business Documents

2021 ◽  
pp. 1030-1044
Author(s):  
Simone Scannapieco ◽  
Andrea Ponza ◽  
Claudio Tomazzoli
Keyword(s):  
Data Extraction

Exit-surface wave reconstruction using a focal series

1992 ◽  
Vol 50 (2) ◽  
pp. 988-989
Author(s):  
W.J. de Ruijter ◽  
M.R. McCartney ◽  
David J. Smith ◽  
J.K. Weiss
Keyword(s):  
Surface Wave ◽  
Spherical Aberration ◽  
Data Extraction ◽  
High Sensitivity ◽  
Geometric Distortion ◽  
Variation Method ◽  
Objective Lens ◽  
Immediate Reconstruction ◽  
Exit Surface ◽  
Electron Microscopes

Further advances in resolution enhancement of transmission electron microscopes can be expected from digital processing of image data recorded with slow-scan CCD cameras. Image recording with these new cameras is essential because of their high sensitivity, extreme linearity and negligible geometric distortion. Furthermore, digital image acquisition allows for on-line processing which yields virtually immediate reconstruction results. At present, the most promising techniques for exit-surface wave reconstruction are electron holography and the recently proposed focal variation method. The latter method is based on image processing applied to a series of images recorded at equally spaced defocus.Exit-surface wave reconstruction using the focal variation method as proposed by Van Dyck and Op de Beeck proceeds in two stages. First, the complex image wave is retrieved by data extraction from a parabola situated in three-dimensional Fourier space. Then the objective lens spherical aberration, astigmatism and defocus are corrected by simply dividing the image wave by the wave aberration function calculated with the appropriate objective lens aberration coefficients which yields the exit-surface wave.

Data Extraction Method from Printed Images with Different Formats

2017 ◽  
Vol E100.A (11) ◽  
pp. 2355-2357
Author(s):  
Mitsuji MUNEYASU ◽  
Nayuta JINDA ◽  
Yuuya MORITANI ◽  
Soh YOSHIDA
Keyword(s):  
Extraction Method ◽  
Data Extraction

A FRAME WORK FOR WEB INFORMATION EXTRACTION AND ANALYSIS

2013 ◽  
Vol 7 (2) ◽  
pp. 574-579 ◽  
Author(s):  
Dr Sunitha Abburu ◽  
G. Suresh Babu
Keyword(s):  
Information Extraction ◽  
Data Extraction ◽  
Research Work ◽  
Web Pages ◽  
Web Documents ◽  
E Learning ◽  
Structured Information ◽  
Frame Work ◽  
Effective Decision ◽  
The Web

Day by day the volume of information availability in the web is growing significantly. There are several data structures for information available in the web such as structured, semi-structured and unstructured. Majority of information in the web is presented in web pages. The information presented in web pages is semi-structured.  But the information required for a context are scattered in different web documents. It is difficult to analyze the large volumes of semi-structured information presented in the web pages and to make decisions based on the analysis. The current research work proposed a frame work for a system that extracts information from various sources and prepares reports based on the knowledge built from the analysis. This simplifies  data extraction, data consolidation, data analysis and decision making based on the information presented in the web pages.The proposed frame work integrates web crawling, information extraction and data mining technologies for better information analysis that helps in effective decision making.   It enables people and organizations to extract information from various sourses of web and to make an effective analysis on the extracted data for effective decision making.  The proposed frame work is applicable for any application domain. Manufacturing,sales,tourisum,e-learning are various application to menction few.The frame work is implemetnted and tested for the effectiveness of the proposed system and the results are promising.

Impact of surgery timing for craniosynostosis on neurodevelopmental outcomes: a systematic review

2019 ◽  
Vol 23 (4) ◽  
pp. 442-454 ◽  
Author(s):  
Rachel Mandela ◽  
Maggie Bellew ◽  
Paul Chumas ◽  
Hannah Nash
Keyword(s):  
Systematic Review ◽  
Beneficial Effect ◽  
Data Extraction ◽  
Sociodemographic Factors ◽  
Future Research ◽  
Neurodevelopmental Outcomes ◽  
Age At Surgery ◽  
Data Extraction Form ◽  
Surgery Timing ◽  
Anesthetic Exposure

OBJECTIVEThere are currently no guidelines for the optimum age for surgical treatment of craniosynostosis. This systematic review summarizes and assesses evidence on whether there is an optimal age for surgery in terms of neurodevelopmental outcomes.METHODSThe databases MEDLINE, PsycINFO, CINAHL, Embase + Embase Classic, and Web of Science were searched between October and November 2016 and searches were repeated in July 2017. According to PICO (participants, intervention, comparison, outcome) criteria, studies were included that focused on: children diagnosed with nonsyndromic craniosynostosis, aged ≤ 5 years at time of surgery; corrective surgery for nonsyndromic craniosynostosis; comparison of age-at-surgery groups; and tests of cognitive and neurodevelopmental postoperative outcomes. Studies that did not compare age-at-surgery groups (e.g., those employing a correlational design alone) were excluded. Data were double-extracted by 2 authors using a modified version of the Cochrane data extraction form.RESULTSTen studies met the specified criteria; 5 found a beneficial effect of earlier surgery, and 5 did not. No study found a beneficial effect of later surgery. No study collected data on length of anesthetic exposure and only 1 study collected data on sociodemographic factors.CONCLUSIONSIt was difficult to draw firm conclusions from the results due to multiple confounding factors. There is some inconclusive evidence that earlier surgery is beneficial for patients with sagittal synostosis. The picture is even more mixed for other subtypes. There is no evidence that later surgery is beneficial. The authors recommend that future research use agreed-upon parameters for: age-at-surgery cut-offs, follow-up times, and outcome measures.

Results of 1940 embolizations for dural arteriovenous fistulas: Japanese Registry of Neuroendovascular Therapy (JR-NET3)

2020 ◽  
Vol 133 (1) ◽  
pp. 166-173 ◽  
Author(s):  
Masafumi Hiramatsu ◽  
Kenji Sugiu ◽  
Tomohito Hishikawa ◽  
Shingo Nishihiro ◽  
Naoya Kidani ◽  
...  
Keyword(s):  
Risk Factors ◽  
Data Extraction ◽  
Transarterial Embolization ◽  
Complication Rates ◽  
Multicenter Observational Study ◽  
Arteriovenous Fistulas ◽  
Emergency Procedures ◽  
Dural Arteriovenous Fistulas ◽  
Nature Frequency ◽  
Independent Risk Factors

OBJECTIVEEmbolization is the most common treatment for dural arteriovenous fistulas (dAVFs). A retrospective, multicenter observational study was conducted in Japan to clarify the nature, frequency, and risk factors for complications of dAVF embolization.METHODSPatient data were derived from the Japanese Registry of Neuroendovascular Therapy 3 (JR-NET3). A total of 40,169 procedures were registered in JR-NET3, including 2121 procedures (5.28%) in which dAVFs were treated with embolization. After data extraction, the authors analyzed complication details and risk factors in 1940 procedures performed in 1458 patients with cranial dAVFs treated with successful or attempted embolization.RESULTSTransarterial embolization (TAE) alone was performed in 858 cases (44%), and transvenous embolization (TVE) alone was performed in 910 cases (47%). Both TAE and TVE were performed in one session in 172 cases (9%). Complications occurred in 149 cases (7.7%). Thirty-day morbidity and mortality occurred in 55 cases (2.8%) and 16 cases (0.8%), respectively. Non–sinus-type locations, radical embolization as the strategy, procedure done at a hospital that performed dAVF embolization in fewer than 10 cases during the study period, and emergency procedures were independent risk factors for overall complications.CONCLUSIONSComplication rates of dAVF embolization in Japan were acceptable. For better results, the risk factors identified in this study should be considered in treatment decisions.

Data Extraction Techniques for Spreadsheet Records

2007 ◽  
Vol 2 (1) ◽  
pp. 119-129 ◽  
Author(s):  
Mark G. Simkin
Keyword(s):  
Data Extraction ◽  
Stratified Sampling ◽  
Specific Information ◽  
Extraction Techniques ◽  
Filtering Techniques

Abstract Many accounting applications use spreadsheets as repositories of accounting records, and a common requirement is the need to extract specific information from them. This paper describes a number of techniques that accountants can use to perform such tasks directly using common spreadsheet tools. These techniques include (1) simple and advanced filtering techniques, (2) database functions, (3) methods for both simple and stratified sampling, and, (4) tools for finding duplicate or unmatched records.

A Systematic Review and Meta-Analysis about the Effect of Bisphosphonates on the Risk of Skeletal-Related Event in Men with Prostate Cancer

2020 ◽  
Vol 20 (13) ◽  
pp. 1604-1612
Author(s):  
Congcong Wu ◽  
Hua Jiang ◽  
Jianghua Chen
Keyword(s):  
Prostate Cancer ◽  
Fixed Effects ◽  
Data Extraction ◽  
Controlled Trial ◽  
Meta Analysis ◽  
Control Group ◽  
Fixed Effects Model ◽  
Related Event ◽  
Mineral Density ◽  
Skeletal Related Event

Background: Although the adjuvant therapy of bisphosphonates in prostate cancer is effective in improving bone mineral density, it is still uncertain whether bisphosphonates could decrease the risk of Skeletal- Related Event (SRE) in patients with prostate cancer. We reviewed and analyzed the effect of different types of bisphosphonates on the risk of SRE, defined as pathological fracture, spinal cord compression, radiation therapy to the bone, surgery to bone, hypercalcemia, bone pain, or death as a result of prostate cancer. Methods: A systemic literature search was conducted on PubMed and related bibliographies. The emphasis during data extraction was laid on the Hazard Ratio (HR) and the corresponding 95% Confidence Interval (CI) from every eligible Randomized Controlled Trial (RCT). HR was pooled with the fixed effects model, and preplanned subgroup analyses were performed. Results: 5 RCTs (n = 4651) were included and analyzed finally after screening 51 articles. The meta-analysis of all participants showed no significant decrease in the risk of SRE when adding bisphosphonates to control group (HR = 0.968, 95% CI = 0.874 - 1.072, p = 0.536) with low heterogeneity (I2 = 0.0% (d.f. = 4) p = 0.679). There was no significant improvement on SRE neither in the subgroups with Metastases (M1) or Castration-Sensitive Prostate Cancer (CSPC) (respectively HR = 0.968, 95% CI = 0.874 - 1.072, p = 0.536, I2 = 0.0% (d.f. = 4) p = 0.679; HR = 0.954, 95% CI = 0.837 - 1.088, p = 0.484, I2 = 0.0% (d.f. = 3) p = 0.534). Conclusion: Our study demonstrated that bisphosphonates could not statistically significantly reduce the risk of SRE in patients with prostate cancer, neither in the subgroups with M1 or CSPC.

Unique views on obesity-related behaviors and environments: research using still and video images (Preprint)

2018 ◽  
Author(s):  
Jordan Carlson ◽  
J. Aaron Hipp ◽  
Jacqueline Kerr ◽  
Todd Horowitz ◽  
David Berrigan
Keyword(s):  
Physical Activity ◽  
Ethical Issues ◽  
Data Extraction ◽  
Dietary Assessment ◽  
Extraction Methods ◽  
Image Capture ◽  
Still Images ◽  
Key Informants ◽  
Technological Advances ◽  
Computer Scientists

BACKGROUND Image based data collection for obesity research is in its infancy. OBJECTIVE The present study aimed to document challenges to and benefits from such research by capturing examples of research involving the use of images to assess physical activity- or nutrition-related behaviors and/or environments. METHODS Researchers (i.e., key informants) using image capture in their research were identified through knowledge and networks of the authors of this paper and through literature search. Twenty-nine key informants completed a survey covering the type of research, source of images, and challenges and benefits experienced, developed specifically for this study. RESULTS Most respondents used still images in their research, with only 26.7% using video. Image sources were categorized as participant generated (N = 13; e.g., participants using smartphones for dietary assessment), researcher generated (N = 10; e.g., wearable cameras with automatic image capture), or curated from third parties (N = 7; e.g., Google Street View). Two of the major challenges that emerged included the need for automated processing of large datasets (58.8%) and participant recruitment/compliance (41.2%). Benefit-related themes included greater perspectives on obesity with increased data coverage (34.6%) and improved accuracy of behavior and environment assessment (34.6%). CONCLUSIONS Technological advances will support the increased use of images in the assessment of physical activity, nutrition behaviors, and environments. To advance this area of research, more effective collaborations are needed between health and computer scientists. In particular development of automated data extraction methods for diverse aspects of behavior, environment, and food characteristics are needed. Additionally, progress in standards for addressing ethical issues related to image capture for research purposes are critical. CLINICALTRIAL NA

Artificial Intelligence for Skin Cancer Detection: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Abdulrahman Takiddin ◽  
Jens Schneider ◽  
Yin Yang ◽  
Alaa Abd-Alrazaq ◽  
Mowafa Househ
Keyword(s):  
Artificial Intelligence ◽  
Skin Cancer ◽  
Scoping Review ◽  
Performance Metrics ◽  
Data Extraction ◽  
Characteristic Curve ◽  
Evaluation Metrics ◽  
Cancer Type ◽  
Computer Algorithms ◽  
Scoping Reviews

BACKGROUND Skin cancer is the most common cancer type affecting humans. Traditional skin cancer diagnosis methods are costly, require a professional physician, and take time. Hence, to aid in diagnosing skin cancer, Artificial Intelligence (AI) tools are being used, including shallow and deep machine learning-based techniques that are trained to detect and classify skin cancer using computer algorithms and deep neural networks. OBJECTIVE The aim of this study is to identify and group the different types of AI-based technologies used to detect and classify skin cancer. The study also examines the reliability of the selected papers by studying the correlation between the dataset size and number of diagnostic classes with the performance metrics used to evaluate the models. METHODS We conducted a systematic search for articles using IEEE Xplore, ACM DL, and Ovid MEDLINE databases following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. The study included in this scoping review had to fulfill several selection criteria; to be specifically about skin cancer, detecting or classifying skin cancer, and using AI technologies. Study selection and data extraction were conducted by two reviewers independently. Extracted data were synthesized narratively, where studies were grouped based on the diagnostic AI techniques and their evaluation metrics. RESULTS We retrieved 906 papers from the 3 databases, but 53 studies were eligible for this review. While shallow techniques were used in 14 studies, deep techniques were utilized in 39 studies. The studies used accuracy (n=43/53), the area under receiver operating characteristic curve (n=5/53), sensitivity (n=3/53), and F1-score (n=2/53) to assess the proposed models. Studies that use smaller datasets and fewer diagnostic classes tend to have higher reported accuracy scores. CONCLUSIONS The adaptation of AI in the medical field facilitates the diagnosis process of skin cancer. However, the reliability of most AI tools is questionable since small datasets or low numbers of diagnostic classes are used. In addition, a direct comparison between methods is hindered by a varied use of different evaluation metrics and image types.

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