Pub Date : 2010-01-01Epub Date: 2011-05-23DOI: 10.1504/IJFIPM.2010.040211
Daniel J Vreeman, Clement J McDonald, Stanley M Huff
In many areas of practice and research, clinical observations are recorded on data collection forms by asking and answering questions, yet without being represented in accepted terminology standards these results cannot be easily shared among clinical care and research systems. LOINC contains a well-developed model for representing variables, answer lists, and the collections that contain them. We have successfully added many assessments and other collections of variables to LOINC in this model. By creating a uniform representation and distributing it worldwide at no cost, LOINC aims to lower the barriers to interoperability among systems and make this valuable data available across settings when and where it is needed.
{"title":"LOINC® - A Universal Catalog of Individual Clinical Observations and Uniform Representation of Enumerated Collections.","authors":"Daniel J Vreeman, Clement J McDonald, Stanley M Huff","doi":"10.1504/IJFIPM.2010.040211","DOIUrl":"10.1504/IJFIPM.2010.040211","url":null,"abstract":"<p><p>In many areas of practice and research, clinical observations are recorded on data collection forms by asking and answering questions, yet without being represented in accepted terminology standards these results cannot be easily shared among clinical care and research systems. LOINC contains a well-developed model for representing variables, answer lists, and the collections that contain them. We have successfully added many assessments and other collections of variables to LOINC in this model. By creating a uniform representation and distributing it worldwide at no cost, LOINC aims to lower the barriers to interoperability among systems and make this valuable data available across settings when and where it is needed.</p>","PeriodicalId":88259,"journal":{"name":"International journal of functional informatics and personalised medicine","volume":"3 4","pages":"273-291"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418707/pdf/nihms361045.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30840819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-01-01DOI: 10.1504/IJFIPM.2009.027587
Tianming Liu, Hanchuan Peng, Xiaobo Zhou
Imaging informatics has emerged as a major research theme in biomedicine in the last few decades. Currently, personalised, predictive and preventive patient care is believed to be one of the top priorities in biomedical research and practice. Imaging informatics plays a major role in biomedicine studies. This paper reviews main applications and challenges of imaging informatics in biomedicine.
{"title":"Imaging informatics for personalised medicine: applications and challenges.","authors":"Tianming Liu, Hanchuan Peng, Xiaobo Zhou","doi":"10.1504/IJFIPM.2009.027587","DOIUrl":"https://doi.org/10.1504/IJFIPM.2009.027587","url":null,"abstract":"<p><p>Imaging informatics has emerged as a major research theme in biomedicine in the last few decades. Currently, personalised, predictive and preventive patient care is believed to be one of the top priorities in biomedical research and practice. Imaging informatics plays a major role in biomedicine studies. This paper reviews main applications and challenges of imaging informatics in biomedicine.</p>","PeriodicalId":88259,"journal":{"name":"International journal of functional informatics and personalised medicine","volume":"2 2","pages":"125-135"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJFIPM.2009.027587","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28463034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-01DOI: 10.1504/IJFIPM.2008.020187
Ying Chen, Joseph Y Lo, James T Dobbins
Breast cancer is second only to lung cancer as the leading cause of non-preventable cancer death in women. Digital Breast Tomosynthesis (DBT) is a promising technique to improve early breast cancer detection. In this paper, we present the impulse response and Modulation Transfer Function (MTF) analysis to quantitatively compare Shift-And-Add (SAA) and point-by-point Back Projection (BP) three-dimensional image reconstruction algorithms in DBT. A Filtered Back Projection (FBP) deblurring algorithm based on point-by-point BP was used to demonstrate deblurred tomosynthesis images.
{"title":"Impulse response and Modulation Transfer Function analysis for Shift-And-Add and Back Projection image reconstruction algorithms in Digital Breast Tomosynthesis (DBT).","authors":"Ying Chen, Joseph Y Lo, James T Dobbins","doi":"10.1504/IJFIPM.2008.020187","DOIUrl":"https://doi.org/10.1504/IJFIPM.2008.020187","url":null,"abstract":"<p><p>Breast cancer is second only to lung cancer as the leading cause of non-preventable cancer death in women. Digital Breast Tomosynthesis (DBT) is a promising technique to improve early breast cancer detection. In this paper, we present the impulse response and Modulation Transfer Function (MTF) analysis to quantitatively compare Shift-And-Add (SAA) and point-by-point Back Projection (BP) three-dimensional image reconstruction algorithms in DBT. A Filtered Back Projection (FBP) deblurring algorithm based on point-by-point BP was used to demonstrate deblurred tomosynthesis images.</p>","PeriodicalId":88259,"journal":{"name":"International journal of functional informatics and personalised medicine","volume":"1 2","pages":"189-204"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJFIPM.2008.020187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31649406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-01DOI: 10.1504/ijfipm.2008.020183
Walker H Land, John J Heine, Tom Raway, Alda Mizaku, Nataliya Kovalchuk, Jack Y Yang, Mary Qu Yang
The automated decision paradigms presented in this work address the false positive (FP) biopsy occurrence in diagnostic mammography. An EP/ES stochastic hybrid and two kernelized Partial Least Squares (K-PLS) paradigms were investigated with following studies: methodology performance comparisonsautomated diagnostic accuracy assessments with two data sets. The findings showed: the new hybrid produced comparable results more rapidlythe new K-PLS paradigms train and operate Essentially in real time for the data sets studied. Both advancements are essential components for eventually achieving the FP reduction goal, while maintaining acceptable diagnostic sensitivities.
{"title":"New statistical learning theory paradigms adapted to breast cancer diagnosis/classification using image and non-image clinical data.","authors":"Walker H Land, John J Heine, Tom Raway, Alda Mizaku, Nataliya Kovalchuk, Jack Y Yang, Mary Qu Yang","doi":"10.1504/ijfipm.2008.020183","DOIUrl":"https://doi.org/10.1504/ijfipm.2008.020183","url":null,"abstract":"<p><p>The automated decision paradigms presented in this work address the false positive (FP) biopsy occurrence in diagnostic mammography. An EP/ES stochastic hybrid and two kernelized Partial Least Squares (K-PLS) paradigms were investigated with following studies: methodology performance comparisonsautomated diagnostic accuracy assessments with two data sets. The findings showed: the new hybrid produced comparable results more rapidlythe new K-PLS paradigms train and operate Essentially in real time for the data sets studied. Both advancements are essential components for eventually achieving the FP reduction goal, while maintaining acceptable diagnostic sensitivities.</p>","PeriodicalId":88259,"journal":{"name":"International journal of functional informatics and personalised medicine","volume":"1 2","pages":"111-139"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/ijfipm.2008.020183","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34056313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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