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Biomedical Informatics Insights

ISSN Print: 1178-2226

ISSN Online:

Website: http://www.la-press.com/biomedical-informatics-insights-journal-j82

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Recognizing Scientific Artifacts in Biomedical Literature

Tudor Groza,Hamed Hassanzadeh,Jane Hunter

Decomposing Phenotype Descriptions for the Human Skeletal Phenome

Tudor Groza,Jane Hunter,Andreas Zankl

Using n-Grams for Syndromic Surveillance in a Turkish Emergency Department Without English Translation: A Feasibility Study

Sylvia Halász,Philip Brown,Cem Oktay,Arif Alper ？evik

Enhancing Disease Surveillance Event Communication Among Jurisdictions

Nathaniel R. Tabernero, Wayne A. Loschen, Joel Jorgensen, Joshua Suereth, Jacqueline S. Coberly, Rekha S. Holtry, Marvin L. Sikes, Steven M. Babin and Sheryl L. Happel Lewis

What’s In a Note: Construction of a Suicide Note Corpus

John P. Pestian, Pawel Matykiewicz and Michelle Linn-Gust

A Hybrid Approach to Sentiment Sentence Classification in Suicide Notes

Sunghwan Sohn, Manabu Torii, Dingcheng Li, Kavishwar Wagholikar, Stephen Wu and Hongfang Liu

Three Hybrid Classifiers for the Detection of Emotions in Suicide Notes

Maria Liakata, Jee-Hyub Kim, Shyamasree Saha, Janna Hastings, and Dietrich Rebholz-Schuhmann

Comparison of LDA and SPRT on Clinical Dataset Classifications

Chih Lee, Brittany Nkounkou and Chun-Hsi Huang

Avoiding Pitfalls in the Statistical Analysis of Heterogeneous Tumors

David E. Axelrod, Naomi Miller and Judith-Anne W. Chapman

Recognizing Scientific Artifacts in Biomedical Literature

Tudor Groza, Hamed Hassanzadeh and Jane Hunter

Personalizing Drug Selection Using Advanced Clinical Decision Support

John Pestian, Malik Spencer, Pawel Matykiewicz, Kejian Zhang, Sander Vinks and Tracy Glauser

Combining Lexico-semantic Features for Emotion Classification in Suicide Notes

Bart Desmet, and Véronique Hoste

Early Fusion of Low Level Features for Emotion Mining

Fabon Dzogang, Marie-Jeanne Lesot, Maria Rifqi, and Bernadette Bouchon-Meunier

A Hybrid Model for Automatic Emotion Recognition in Suicide Notes

Hui Yang, Alistair Willis, Anne de Roeck and Bashar Nuseibeh

Statistical and Similarity Methods for Classifying Emotion in Suicide Notes

Kirk Roberts and Sanda M. Harabagiu

Artificial Neural Networks for Early Prediction of Mortality in Patients with Non Variceal Upper GI Bleeding (UGIB)

Enzo Grossi, Riccardo Marmo, Marco Intraligi and Massimo Buscema

Fine-Grained Emotion Detection in Suicide Notes: A Thresholding Approach to Multi-Label Classification

Kim Luyckx, Frederik Vaassen, Claudia Peersman and Walter Daelemans

Differential Transcriptional Changes in Mice Exposed to Chemically Distinct Diesel Samples

Tina Stevens, Susan Hester and M. Ian Gilmour

Topic Categorisation of Statements in Suicide Notes with Integrated Rules and Machine Learning

Aleksandar Kovacevic, Azad Dehghan, John A. Keane and Goran Nenadic

Labeling Emotions in Suicide Notes: Cost-Sensitive Learning with Heterogeneous Features

Jonathon Read, Erik Velldal and Lilja vrelid

Suicide Note Classification Using Natural Language Processing: A Content Analysis

John Pestian, Henry Nasrallah, Pawel Matykiewicz, Aurora Bennett and Antoon Leenaars

Current Challenge in Consumer Health Informatics: Bridging the Gap between Access to Information and Information Understanding

Laurence Alpay, John Verhoef, Bo Xie, Dov Te’eni and J.H.M. Zwetsloot-Schonk

HIPAA, HIPAA, Hooray? Current Challenges and Initiatives in Health Informatics in the United States

Sanjaya Joshi

A Hybrid System for Emotion Extraction from Suicide Notes

Azadeh Nikfarjam, Ehsan Emadzadeh and Graciela Gonzalez

Rule-based and Lightly Supervised Methods to Predict Emotions in Suicide Notes

Ted Pedersen

Binary Classifiers and Latent Sequence Models for Emotion Detection in Suicide Notes

Colin Cherry, Saif M. Mohammad and Berry de Bruijn

Leveraging Psycholinguistic Resources and Emotional Sequence Models for Suicide Note Emotion Annotation

Eric Yeh, William Jarrold and Joshua Jordan

A Na ve Bayes Approach to Classifying Topics in Suicide Notes

Irena Spasic, Pete Burnap, Mark Greenwood and Michael Arribas-Ayllon

Emotion Detection in Suicide Notes using Maximum Entropy Classification

Richard Wicentowski and Matthew R. Sydes

Introductory Editorial

John P. Pestian

LASSA: Emotion Detection via Information Fusion

Ning Yu, Sandra Kübler, Joshua Herring, Yu-Yin Hsu, Ross Israel and Charese Smiley

Suicide Note Sentiment Classification: A Supervised Approach Augmented by Web Data

Yan Xu, Yue Wang,, Jiahua Liu, Zhuowen Tu, Jian-Tao Sun, Junichi Tsujii and Eric Chang

Using Ensemble Models to Classify the Sentiment Expressed in Suicide Notes

James A. McCart, Dezon K. Finch, Jay Jarman, Edward Hickling, Jason D. Lind, Matthew R. Richardson, Donald J. Berndt and Stephen L. Luther

A Combined Approach to Emotion Detection in Suicide Notes

Alexander Pak, Delphine Bernhard, Patrick Paroubek and Cyril Grouin

Discovering Fine-grained Sentiment in Suicide Notes

Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang and Amit P. Sheth

Decomposing Phenotype Descriptions for the Human Skeletal Phenome

Tudor Groza, Jane Hunter and Andreas Zankl

A Method to Detect Differential Gene Expression in Cross-Species Hybridization Experiments at Gene and Probe Level

Ying Chen, Rebekah Wu, James Felton, David M. Rocke and Anu Chakicherla

Experiences from the Architectural Migration of a Joint Replacement Surgery Information System

Samuli Niiranen, Ari V lim li and Jari Yli-Hietanen

Risk Judgment by General Dental Practitioners: Rational but Uninformed

Eva Ellervall, Berndt Brehmer and Kerstin Knutsson

Sentiment Analysis of Suicide Notes: A Shared Task

John P. Pestian, Pawel Matykiewicz, Michelle Linn-Gust, Brett South, Ozlem Uzuner, Jan Wiebe, Kevin B. Cohen, John Hurdle, Christopher Brew

Closing the Loop: Facilitating the Use of Autopsy Information in Medical Decision Making and Managed Care

Peter N. Nemetz

Planning for Hospital IT Implementation: A New Look at the Business Case

Nir Menachemi, Ebrahim Randeree, Darrell E. Burke and Eric W. Ford

LASSA: Emotion Detection via Information Fusion

Ning Yu,Sandra Kübler,Joshua Herring,Yu-Yin Hsu

Statistical and Similarity Methods for Classifying Emotion in Suicide Notes

Kirk Roberts,Sanda M. Harabagiu

Suicide Note Sentiment Classification: A Supervised Approach Augmented by Web Data

Yan Xu,Yue Wang,,Jiahua Liu,Zhuowen Tu

Rule-based and Lightly Supervised Methods to Predict Emotions in Suicide Notes

Ted Pedersen

Discovering Fine-grained Sentiment in Suicide Notes

Wenbo Wang,Lu Chen,Ming Tan,Shaojun Wang

What’s In a Note: Construction of a Suicide Note Corpus

John P. Pestian,Pawel Matykiewicz,Michelle Linn-Gust

Three Hybrid Classifiers for the Detection of Emotions in Suicide Notes

Maria Liakata,Jee-Hyub Kim,Shyamasree Saha,Janna Hastings

Combining Lexico-semantic Features for Emotion Classification in Suicide Notes

Bart Desmet,Véronique Hoste

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