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Machine Learning for Health Informatics

Overview of attention for book
Cover of 'Machine Learning for Health Informatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Machine Learning for Health Informatics
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    Chapter 2 Bagging Soft Decision Trees
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    Chapter 3 Grammars for Discrete Dynamics
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    Chapter 4 Empowering Bridging Term Discovery for Cross-Domain Literature Mining in the TextFlows Platform
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    Chapter 5 Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice
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    Chapter 6 Deep Learning Trends for Focal Brain Pathology Segmentation in MRI
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    Chapter 7 Differentiation Between Normal and Epileptic EEG Using K-Nearest-Neighbors Technique
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    Chapter 8 Survey on Feature Extraction and Applications of Biosignals
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    Chapter 9 Argumentation for Knowledge Representation, Conflict Resolution, Defeasible Inference and Its Integration with Machine Learning
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    Chapter 10 Machine Learning and Data Mining Methods for Managing Parkinson’s Disease
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    Chapter 11 Challenges of Medical Text and Image Processing: Machine Learning Approaches
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    Chapter 12 Visual Intelligent Decision Support Systems in the Medical Field: Design and Evaluation
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    Chapter 13 A Master Pipeline for Discovery and Validation of Biomarkers
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    Chapter 14 Machine Learning Solutions in Computer-Aided Medical Diagnosis
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    Chapter 15 Processing Neurology Clinical Data for Knowledge Discovery: Scalable Data Flows Using Distributed Computing
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    Chapter 16 Network-Guided Biomarker Discovery
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    Chapter 17 Knowledge Discovery in Clinical Data
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    Chapter 18 Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning
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    Chapter 19 Convolutional Neural Networks Applied for Parkinson’s Disease Identification
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    Chapter 20 Recommender Systems for Health Informatics: State-of-the-Art and Future Perspectives
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    Chapter 21 Machine Learning for In Silico Modeling of Tumor Growth
  23. Altmetric Badge
    Chapter 22 A Tutorial on Machine Learning and Data Science Tools with Python
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
35 X users
patent
1 patent

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
133 Mendeley
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Title
Machine Learning for Health Informatics
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-50478-0
ISBNs
978-3-31-950477-3, 978-3-31-950478-0
Editors

Andreas Holzinger

X Demographics

X Demographics

The data shown below were collected from the profiles of 35 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 133 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 18%
Student > Ph. D. Student 21 16%
Researcher 14 11%
Student > Bachelor 13 10%
Student > Postgraduate 6 5%
Other 21 16%
Unknown 34 26%
Readers by discipline Count As %
Computer Science 44 33%
Engineering 19 14%
Medicine and Dentistry 7 5%
Business, Management and Accounting 4 3%
Agricultural and Biological Sciences 3 2%
Other 17 13%
Unknown 39 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 February 2022.
All research outputs
#1,530,324
of 24,396,012 outputs
Outputs from Lecture notes in computer science
#233
of 8,155 outputs
Outputs of similar age
#26,975
of 402,841 outputs
Outputs of similar age from Lecture notes in computer science
#55
of 582 outputs
Altmetric has tracked 24,396,012 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,155 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,841 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 582 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.