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Table of Contents

2020 IEEE journal of biomedical and health informatics  
Wang 2912 Medical Informatics EMR-Based Phenotyping of Ischemic Stroke Using Supervised Machine Learning and Text Mining Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Zou, and F. Guo 3012 A Deep Learning-Based Chemical System for QSAR Prediction . . . . . . . . . . . . . . . . S. S. Hu, P. Chen, P. Gu, and B.  ... 
doi:10.1109/jbhi.2020.3026857 fatcat:hcw5jrma3jasfbk7nz2ndvyaam

Patient representation from structured electronic medical records based on embedding technique (Preprint)

Yanqun Huang, Ni Wang, Zhiqiang Zhang, Honglei Liu, Xiaolu Fei, Lan Wei, Hui Chen
2020 JMIR Medical Informatics  
The patient-level embedding-based representation is easy to use as continuous input to standard machine learning algorithms and can bring performance improvements.  ...  Objective: We aimed to apply the embedding technique used in the natural language processing domain for the sEMR data representation and to explore the feasibility and superiority of the embedding-based  ...  Acknowledgments This work was supported by the National Natural Science Foundation of China (grants 81971707 and 81701792).  ... 
doi:10.2196/19905 fatcat:fv73ftfvojd7zctebe7yq6df6e

Machine Learning Techniques for Biomedical Natural Language Processing: A comprehensive Review

Essam H. Houssein, Rehab E. Mohamed, Abdelmgeid A. Ali
2021 IEEE Access  
Moreover, this review summarizes the utilizing of Deep Learning and Machine Learning techniques in biomedical NLP tasks based on chronic diseases related EHR data.  ...  We review some of the biomedical NLP methods and systems used over EHRs and give an overview of machine learning and deep learning methodologies used to process EHRs and improve the understanding of the  ...  MACHINE LEARNING TECHNIQUES There are two main categories of learning techniques of machine learning algorithms: supervised learning and unsupervised learning.  ... 
doi:10.1109/access.2021.3119621 fatcat:pl7h35nvqngk3gxpbdxvrgzg2u

Applications of Artificial Intelligence in Healthcare

Shagufta Quazi, Rudra Prasad Saha, Manoj Kumar Singh
2022 Journal of Experimental Biology and Agricultural Sciences  
In Artificial Intelligence, there are two key categories: machine learning (ML) and natural language processing (NPL), both of which are necessary to achieve practically any aim in healthcare.  ...  It has many applications in diagnosis, robotic surgeries, and research, powered by the growing availability of healthcare facts and brisk improvement of analytical techniques.  ...  Machine learning programs may be able to distinguish an ischemic stroke from a hemorrhagic or any other type of stroke, reducing the risk of ignoring cases such as meningitis, coma, encephalitis, acute  ... 
doi:10.18006/2022.10(1).211.226 fatcat:43lctc3oa5gpfptrhcrnbvo5s4

Mining Electronic Health Records (EHRs)

Pranjul Yadav, Michael Steinbach, Vipin Kumar, Gyorgy Simon
2018 ACM Computing Surveys  
With this foundation, we then provide a systematic and methodological organization of existing data mining techniques used to model EHRs and discuss ideas for future research.  ...  In this manuscript, we provide a structured and comprehensive overview of data mining techniques for modeling EHR data.  ...  Phenotyping algorithms can be hand-crafted or machine learned and examples of T2DM phenotyping algorithms include [357, 359, 360] .  ... 
doi:10.1145/3127881 fatcat:xil7qev3xbf3pmfv5vtak4f2jq

2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24

2020 IEEE journal of biomedical and health informatics  
., and Inan, O.T., A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning; JBHI May 2020 1296-1309 Herskovic, V., see Saint-Pierre  ...  Rubin, D. 2570-2579 Jiang, D., see 2473-2480 Jiang, H., see 2798-2805 Jiang, H., Yang, M., Chen, X., Li, M., Li, Y., and Wang, J., miRTMC: A miRNA Target Prediction Method Based on Matrix Completion  ...  ., +, JBHI Nov. 2020 3182-3188 EMR-Based Phenotyping of Ischemic Stroke Using Supervised Machine Learning and Text Mining Techniques.  ... 
doi:10.1109/jbhi.2020.3048808 fatcat:iifrkwtzazdmboabdqii7x5ukm

Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives

Imon Banerjee, Michael Francis Gensheimer, Douglas J. Wood, Solomon Henry, Sonya Aggarwal, Daniel T. Chang, Daniel L. Rubin
2018 Scientific Reports  
In a single framework, we integrated semantic data mapping and neural embedding technique to produce a text processing method that extracts relevant information from heterogeneous types of clinical notes  ...  The high accuracy and explain-ability of the PPES-Met model may enable our model to be used as a decision support tool to personalize metastatic cancer treatment and provide valuable assistance to the  ...  Batch normalization and dropout were mainly applied to achieve a faster learning and higher overall accuracy.  ... 
doi:10.1038/s41598-018-27946-5 pmid:29968730 pmcid:PMC6030075 fatcat:qeizqk3zyjemzlquzbj6jnzk4u

Linking glycemic dysregulation in diabetes to symptoms, comorbidities, and genetics through EHR data mining

Isa Kristina Kirk, Christian Simon, Karina Banasik, Peter Christoffer Holm, Amalie Dahl Haue, Peter Bjødstrup Jensen, Lars Juhl Jensen, Cristina Leal Rodríguez, Mette Krogh Pedersen, Robert Eriksson, Henrik Ullits Andersen, Thomas Almdal (+9 others)
2019 eLife  
Text mining the electronic health records of 14,017 patients, we matched two controlled vocabularies (ICD-10 and a custom vocabulary developed at the clinical center Steno Diabetes Center Copenhagen) to  ...  Diabetes is a diverse and complex disease, with considerable variation in phenotypic manifestation and severity.  ...  Learning vector representation of medical objects via EMR- driven nonnegative restricted Boltzmann machines (eNRBM).  ... 
doi:10.7554/elife.44941 pmid:31818369 fatcat:wtsnydn46bfn5ojgxvlv2axnpi

Health—exploring complexity: an interdisciplinary systems approach HEC2016

Eva Grill, Martin Müller, Ulrich Mansmann
2016 European Journal of Epidemiology  
The system infers sedentary behaviors by means of a supervised Machine Learning Classifier.  ...  The strength of this approach is that it utilizes advanced machine learning techniques training translation models on monolingual and bilingual resources in specific domains.  ...  In this context, a focused crawler uses techniques from the field of machine learning to estimate the relevance of a webpage for the domain of interest [5,6].  ... 
doi:10.1007/s10654-016-0183-1 pmid:27522353 fatcat:dcl3nbpygvh5fg7keri74h55ie


Magda Shaheen, Senait Teklehaimanot
2017 Journal of Clinical and Translational Science  
The use of mental health and antidepressant drug were used to indicate the service use.  ...  For the use of mental health services and/or antidepressant drug among the depressed group, 40–59 years old, AA, Hispanics, uninsured, foreign born were less likely to use mental health services and/or  ...  We used the Community-Engaged Research Navigation model to establish a multisite deidentified database extracted from EHRs of female adolescents aged 12-21 years (January 2011-December 2012) and their  ... 
doi:10.1017/cts.2017.287 fatcat:yp5uxjopfzhuzovziwsbbhl2au

5th European Congress on eCardiology and eHealth (Abstract book) (text is available in electronic version)

article Editorial
2018 Russian Journal of Cardiology  
A simplified cluster sampling technique was used to randomly select mothers who had used MoTeCH from 9 clusters of 64 mothers each, between June-October, 2017.  ...  In this work, we present and validate a method that can quantify the AA perimeter automatically using deep learning. Methods.  ...  To train algorithms we currently use deep learning techniques as those produce state of the art results.  ... 
doaj:11a9913f677d4e3b8e476244b9c6f87f fatcat:ild2xmkdufg7np4f4aqtft6sry

CARS 2016—Computer Assisted Radiology and Surgery Proceedings of the 30th International Congress and Exhibition Heidelberg, Germany, June 21–25, 2016

2016 International Journal of Computer Assisted Radiology and Surgery  
We would like to thank the Spanish company BQ for the donation of the 3D printing hardware for clinical use.  ...  Acknowledgments The authors wish to thank Fundación CEIBA and Alcaldía Mayor de Bogotá, for the financial support of Ricardo Mendoza's PhD studies through the scholarship program ''Becas Rodolfo Llinás  ...  New sensing devices, image recognition techniques, machine learning, use of big data, and the Internet of Medical Things are all part of the new interoperable mobile computing field that has grown as an  ... 
doi:10.1007/s11548-016-1412-5 pmid:27206418 fatcat:uk5r46n2xvhedkfjzmeiweyneq

Redressing Underrecognition of "Cold Drink Heart": Patients Teaching Physicians about Atrial Fibrillation Triggered by Cold Drink and Food

David Vinson
2020 The Permanente Journal  
Acknowledgments We thank our neuromuscular clinic coordinator Susan George-Rydberg, BSN, RN, MA, for helping us identify suitable candidates for study and for managing their cases.  ...  How to Cite this Article No sources of funding to report. Acknowledgments Pamela Schaff, MD, PhD, and Erika Wright PhD contributed preliminary critical reviews of the final manuscript.  ...  ere is great potential for improvement in these models as new machine learning methods continue to be developed, data stored in electronic medical records continue to grow, and text mining and natural  ... 
doi:10.7812/tpp/19.238 fatcat:62vosmkefrf55f72lutiwqavyy

International Academy of Cardiology 18th World Congress on Heart Disease Annual Scientific Sessions 2013. Vancouver, B.C., Canada, July 26-29, 2013

2013 Cardiology  
Acceptance for presentation was based on the average score of all reviewers.  ...  A large number of excellent contributions were received and we thank both contributors and reviewers for their support, interest and effort. Abstract No.  ...  needs, well-phenotyped clinical cohorts, establishment of quality-assured, state-of-the-art platforms for biological interrogation, and rigorous data mining -Translation of technology platforms that can  ... 
doi:10.1159/000354059 pmid:23887240 fatcat:4lu7jkkfcjbjla6g5rx3p242r4

Abstracts of the 27th Congress of the World Society of Cardiovascular and Thoracic Surgeons (WSCTS)

2017 Journal of Cardiothoracic Surgery  
We check for stroke and cranial tomography. Results: The mean age was 65 years, with 75% males, mean CPB time was 63 minutes and mean extubation time was 9.54 hours.  ...  Was evaluated in the postoperative cognitive alterations, Patients were analyzed on the fifth postoperative day, in relation to the cognitive evaluation with questionnaire of questions and memorization  ...  ischemic stroke.  ... 
doi:10.1186/s13019-017-0662-9 fatcat:sym5vpmkzzcurc53ic5ro6crtq
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