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"Natural Language Processing"

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https://www.readbyqxmd.com/read/28227053/the-effects-of-deep-network-topology-on-mortality-prediction
#1
Hao Du, Mohammad M Ghassemi, Mengling Feng, Hao Du, Mohammad M Ghassemi, Mengling Feng, Mengling Feng, Hao Du, Mohammad M Ghassemi
Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attention only in recent years, and it's ultimate place at the bedside remains a topic of skeptical discussion. While there is a growing academic interest in the application of Machine Learning (ML) techniques to clinical problems, many in the clinical community see little incentive to upgrade from simpler methods, such as logistic regression, to deep learning...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227035/visualizing-patient-journals-by-combining-vital-signs-monitoring-and-natural-language-processing
#2
Adnan Vilic, John Asger Petersen, Karsten Hoppe, Helge B D Sorensen, Adnan Vilic, John Asger Petersen, Karsten Hoppe, Helge B D Sorensen, John Asger Petersen, Adnan Vilic, Karsten Hoppe, Helge B D Sorensen
This paper presents a data-driven approach to graphically presenting text-based patient journals while still maintaining all textual information. The system first creates a timeline representation of a patients' physiological condition during an admission, which is assessed by electronically monitoring vital signs and then combining these into Early Warning Scores (EWS). Hereafter, techniques from Natural Language Processing (NLP) are applied on the existing patient journal to extract all entries. Finally, the two methods are combined into an interactive timeline featuring the ability to see drastic changes in the patients' health, and thereby enabling staff to see where in the journal critical events have taken place...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226908/s2ni-a-mobile-platform-for-nutrition-monitoring-from-spoken-data
#3
Niloofar Hezarjaribi, Cody A Reynolds, Drew T Miller, Naomi Chaytor, Hassan Ghasemzadeh, Niloofar Hezarjaribi, Cody A Reynolds, Drew T Miller, Naomi Chaytor, Hassan Ghasemzadeh, Hassan Ghasemzadeh, Cody A Reynolds, Naomi Chaytor, Niloofar Hezarjaribi, Drew T Miller
Diet and physical activity are important lifestyle and behavioral factors in self-management and prevention of many chronic diseases. Mobile sensors such as accelerometers have been used in the past to objectively measure physical activity or detect eating time. Diet monitoring, however, still relies on self-recorded data by end users where individuals use mobile devices for recording nutrition intake by either entering text or taking images. Such approaches have shown low adherence in technology adoption and achieve only moderate accuracy...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28224131/tashkeela-novel-corpus-of-arabic-vocalized-texts-data-for-auto-diacritization-systems
#4
Taha Zerrouki, Amar Balla
Arabic diacritics are often missed in Arabic scripts. This feature is a handicap for new learner to read َArabic, text to speech conversion systems, reading and semantic analysis of Arabic texts. The automatic diacritization systems are the best solution to handle this issue. But such automation needs resources as diactritized texts to train and evaluate such systems. In this paper, we describe our corpus of Arabic diacritized texts. This corpus is called Tashkeela. It can be used as a linguistic resource tool for natural language processing such as automatic diacritics systems, dis-ambiguity mechanism, features and data extraction...
April 2017: Data in Brief
https://www.readbyqxmd.com/read/28217974/home-health-care-nurse-physician-communication-patient-severity-and-hospital-readmission
#5
Michael F Pesko, Linda M Gerber, Timothy R Peng, Matthew J Press
OBJECTIVE: To evaluate whether communication failures between home health care nurses and physicians during an episode of home care after hospital discharge are associated with hospital readmission, stratified by patients at high and low risk of readmission. DATA SOURCE/STUDY SETTING: We linked Visiting Nurse Services of New York electronic medical records for patients with congestive heart failure in 2008 and 2009 to hospitalization claims data for Medicare fee-for-service beneficiaries...
February 19, 2017: Health Services Research
https://www.readbyqxmd.com/read/28209197/accuracy-and-generalizability-of-using-automated-methods-for-identifying-adverse-events-from-electronic-health-record-data-a-validation-study-protocol
#6
Christian M Rochefort, David L Buckeridge, Andréanne Tanguay, Alain Biron, Frédérick D'Aragon, Shengrui Wang, Benoit Gallix, Louis Valiquette, Li-Anne Audet, Todd C Lee, Dev Jayaraman, Bruno Petrucci, Patricia Lefebvre
BACKGROUND: Adverse events (AEs) in acute care hospitals are frequent and associated with significant morbidity, mortality, and costs. Measuring AEs is necessary for quality improvement and benchmarking purposes, but current detection methods lack in accuracy, efficiency, and generalizability. The growing availability of electronic health records (EHR) and the development of natural language processing techniques for encoding narrative data offer an opportunity to develop potentially better methods...
February 16, 2017: BMC Health Services Research
https://www.readbyqxmd.com/read/28207397/stacked-learning-to-search-for-scene-labeling
#7
Feiyang Cheng, Xuming He, Hong Zhang
Search-based structured prediction methods have shown promising successes in both computer vision and natural language processing recently. However, most existing search-based approaches lead to a complex multi-stage learning process, which is ill-suited for scene labeling problems with a high-dimensional output space. In this paper, a stacked learning to search method is proposed to address scene labeling tasks. We design a simplified search process consisting of a sequence of ranking functions, which are learned based on a stacked learning strategy to prevent over-fitting...
February 13, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28203249/autism-spectrum-disorder-detection-from-semi-structured-and-unstructured-medical-data
#8
Jianbo Yuan, Chester Holtz, Tristram Smith, Jiebo Luo
Autism spectrum disorder (ASD) is a developmental disorder that significantly impairs patients' ability to perform normal social interaction and communication. Moreover, the diagnosis procedure of ASD is highly time-consuming, labor-intensive, and requires extensive expertise. Although there exists no known cure for ASD, there is consensus among clinicians regarding the importance of early intervention for the recovery of ASD patients. Therefore, to benefit autism patients by enhancing their access to treatments such as early intervention, we aim to develop a robust machine learning-based system for autism detection by using Natural Language Processing techniques based on information extracted from medical forms of potential ASD patients...
December 2017: EURASIP Journal on Bioinformatics & Systems Biology
https://www.readbyqxmd.com/read/28163196/extraction-of-left-ventricular-ejection-fraction-information-from-various-types-of-clinical-reports
#9
Youngjun Kim, Jennifer H Garvin, Mary K Goldstein, Tammy S Hwang, Andrew Redd, Dan Bolton, Paul A Heidenreich, Stéphane M Meystre
Efforts to improve the treatment of congestive heart failure, a common and serious medical condition, include the use of quality measures to assess guideline-concordant care. The goal of this study is to identify left ventricular ejection fraction (LVEF) information from various types of clinical notes, and to then use this information for heart failure quality measurement. We analyzed the annotation differences between a new corpus of clinical notes from the Echocardiography, Radiology, and Text Integrated Utility package and other corpora annotated for natural language processing (NLP) research in the Department of Veterans Affairs...
February 2, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28155671/identifying-the-missing-proteins-in-human-proteome-by-biological-language-model
#10
Qiwen Dong, Kai Wang, Xuan Liu
BACKGROUND: With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project...
December 23, 2016: BMC Systems Biology
https://www.readbyqxmd.com/read/28152842/measuring-adherence-to-a-choosing-wisely-recommendation-in-a-regional-oncology-clinic
#11
Gary H Lyman, Karma L Kreizenbeck, Catherine R Fedorenko, April Alfiler, Heather Noble, Tracy Kusnir-Wong, Ada Mohedano, F Marc Stewart, Benjamin E Greer, Scott David Ramsey
: 196 Background: Natural language processing (NLP) has the potential to significantly ease the burden of manual abstraction of unstructured electronic text when measuring adherence to national guidelines. We incorporated NLP into standard data processing techniques such as manual abstraction and database queries in order to more efficiently evaluate a regional oncology clinic's adherence to ASCO's Choosing Wisely colony stimulating factor (CSF) recommendation using clinical, billing, and cancer registry data...
March 2016: Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology
https://www.readbyqxmd.com/read/28148472/using-social-listening-data-to-monitor-misuse-and-nonmedical-use-of-bupropion-a-content-analysis
#12
Laurie S Anderson, Heidi G Bell, Michael Gilbert, Julie E Davidson, Christina Winter, Monica J Barratt, Beta Win, Jeffery L Painter, Christopher Menone, Jonathan Sayegh, Nabarun Dasgupta
BACKGROUND: The nonmedical use of pharmaceutical products has become a significant public health concern. Traditionally, the evaluation of nonmedical use has focused on controlled substances with addiction risk. Currently, there is no effective means of evaluating the nonmedical use of noncontrolled antidepressants. OBJECTIVE: Social listening, in the context of public health sometimes called infodemiology or infoveillance, is the process of identifying and assessing what is being said about a company, product, brand, or individual, within forms of electronic interactive media...
1, 2017: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/28140627/performance-of-a-machine-learning-classifier-of-knee-mri-reports-in-two-large-academic-radiology-practices-a-tool-to-estimate-diagnostic-yield
#13
Saeed Hassanpour, Curtis P Langlotz, Timothy J Amrhein, Nicholas T Befera, Matthew P Lungren
OBJECTIVE: The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices. MATERIALS AND METHODS: An NLP system that uses terms and patterns in manually classified narrative knee MRI reports was constructed. The NLP system was trained and tested on expert-classified knee MRI reports from two major health care organizations...
January 31, 2017: AJR. American Journal of Roentgenology
https://www.readbyqxmd.com/read/28113882/cross-domain-recognition-by-identifying-joint-subspaces-of-source-domain-and-target-domain
#14
Yuewei Lin, Jing Chen, Yu Cao, Youjie Zhou, Lingfeng Zhang, Yuan Yan Tang, Song Wang
This paper introduces a new method to solve the cross-domain recognition problem. Different from the traditional domain adaption methods which rely on a global domain shift for all classes between the source and target domains, the proposed method is more flexible to capture individual class variations across domains. By adopting a natural and widely used assumption that the data samples from the same class should lay on an intrinsic low-dimensional subspace, even if they come from different domains, the proposed method circumvents the limitation of the global domain shift, and solves the cross-domain recognition by finding the joint subspaces of the source and target domains...
March 21, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28111640/identifying-peripheral-arterial-disease-cases-using-natural-language-processing-of-clinical-notes
#15
Naveed Afzal, Sunghwan Sohn, Sara Abram, Hongfang Liu, Iftikhar J Kullo, Adelaide M Arruda-Olson
Peripheral arterial disease (PAD) is a chronic disease that affects millions of people worldwide. Ascertaining PAD status from clinical notes by manual chart review is labor intensive and time consuming. In this paper, we describe a natural language processing (NLP) algorithm for automated ascertainment of PAD status from clinical notes using predetermined criteria. We developed and evaluated our system against a gold standard that was created by medical experts based on manual chart review. Our system ascertained PAD status from clinical notes with high sensitivity (0...
February 2016: ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28110055/adverse-and-hypersensitivity-reactions-to-prescription-nonsteroidal-anti-inflammatory-agents-in-a-large-health-care-system
#16
Kimberly G Blumenthal, Kenneth H Lai, Mingshu Huang, Zachary S Wallace, Paige G Wickner, Li Zhou
BACKGROUND: Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most frequently used medications in the United States. NSAID use can be limited by adverse drug reactions (ADRs), including hypersensitivity reactions (HSRs). OBJECTIVE: We aimed to use electronic health record data to determine the incidence and predictors of HSRs to prescription NSAIDs. METHODS: We performed a retrospective cohort study of all adult outpatients in a large health care system prescribed diclofenac, indomethacin, nabumetone, or piroxicam between January 1, 2004, and September 30, 2012...
January 18, 2017: Journal of Allergy and Clinical Immunology in Practice
https://www.readbyqxmd.com/read/28104580/leveraging-electronic-health-care-record-information-to-measure-pressure-ulcer-risk-in-veterans-with-spinal-cord-injury-a-longitudinal-study-protocol
#17
Stephen L Luther, Susan S Thomason, Sunil Sabharwal, Dezon K Finch, James McCart, Peter Toyinbo, Lina Bouayad, Michael E Matheny, Glenn T Gobbel, Gail Powell-Cope
BACKGROUND: Pressure ulcers (PrUs) are a frequent, serious, and costly complication for veterans with spinal cord injury (SCI). The health care team should periodically identify PrU risk, although there is no tool in the literature that has been found to be reliable, valid, and sensitive enough to assess risk in this vulnerable population. OBJECTIVE: The immediate goal is to develop a risk assessment model that validly estimates the probability of developing a PrU...
January 19, 2017: JMIR Research Protocols
https://www.readbyqxmd.com/read/28096249/natural-language-processing-to-extract-symptoms-of-severe-mental-illness-from-clinical-text-the-clinical-record-interactive-search-comprehensive-data-extraction-cris-code-project
#18
Richard G Jackson, Rashmi Patel, Nishamali Jayatilleke, Anna Kolliakou, Michael Ball, Genevieve Gorrell, Angus Roberts, Richard J Dobson, Robert Stewart
OBJECTIVES: We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research. DESIGN: Development and validation of information extraction applications for ascertaining symptoms of SMI in routine mental health records using the Clinical Record Interactive Search (CRIS) data resource; description of their distribution in a corpus of discharge summaries...
January 17, 2017: BMJ Open
https://www.readbyqxmd.com/read/28062392/variations-in-facebook-posting-patterns-across-validated-patient-health-conditions-a-prospective-cohort-study
#19
Robert J Smith, Patrick Crutchley, H Andrew Schwartz, Lyle Ungar, Frances Shofer, Kevin A Padrez, Raina M Merchant
BACKGROUND: Social media is emerging as an insightful platform for studying health. To develop targeted health interventions involving social media, we sought to identify the patient demographic and disease predictors of frequency of posting on Facebook. OBJECTIVE: The aims were to explore the language topics correlated with frequency of social media use across a cohort of social media users within a health care setting, evaluate the differences in the quantity of social media postings across individuals with different disease diagnoses, and determine if patients could accurately predict their own levels of social media engagement...
January 6, 2017: Journal of Medical Internet Research
https://www.readbyqxmd.com/read/28060227/preoperative-opioid-use-is-associated-with-early-revision-after-total-knee-arthroplasty-a-study-of-male-patients-treated-in-the-veterans-affairs-system
#20
Alon Ben-Ari, Howard Chansky, Irene Rozet
BACKGROUND: Opioid use is endemic in the U.S. and is associated with morbidity and mortality. The impact of long-term opioid use on joint-replacement outcomes remains unknown. We tested the hypothesis that use of opioids is associated with adverse outcomes after total knee arthroplasty (TKA). METHODS: We performed a retrospective analysis of patients who had had TKA within the U.S. Veterans Affairs (VA) system over a 6-year period and had been followed for 1 year postoperatively...
January 4, 2017: Journal of Bone and Joint Surgery. American Volume
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