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Predictive Analytics of Psychological Disorders in Healthcare

Overview of attention for book
Predictive Analytics of Psychological Disorders in Healthcare
Springer Nature Singapore

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Predictive Analysis of Psychological Disorders on Health
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    Chapter 2 The Rising Aesthetic Concern with Digitalization: Qualitative Evidences from Turkey
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    Chapter 3 AI-Based Predictive Analytics for Patients’ Psychological Disorder
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    Chapter 4 Monitoring the Impact of Stress on Facial Skin Using Affective Computing
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    Chapter 5 Computational Techniques in Prognostic and Data Modelling of Mentally Ill Patients with Special Emphasis on Post-COVID-19 Scenario
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    Chapter 6 Predicting Depression Through Social Media
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    Chapter 7 COVID-19 Impact on Online Learning: A Statistical and Machine Learning Model Analysis for Stress Detection
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    Chapter 8 Measuring Mental Health at Workplaces Using Machine Learning Techniques
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    Chapter 9 Old Age People Emotional Stress Prediction During Outbreak Using Machine Learning Methods
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    Chapter 10 Unlocking the Psychological Toolbox: To Transform or to Sustain
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    Chapter 11 Sentimental Analysis of Fears, Psychological Disorders and Health Issues Through NVIVO During Second Wave of Covid-19
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    Chapter 12 Tertiary Students Stress Detection During Online Learning in Jos, Nigeria
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    Chapter 13 Prediction of Mental Health in Cancer Patients Using Ensemble Machine Learning
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    Chapter 14 Alzheimer’s Disease Classification Using Feed Forwarded Deep Neural Networks for Brain MRI Images
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    Chapter 15 Challenges and Privacy Concerns Related to Use of Information Technology in Mental Healthcare
Attention for Chapter 15: Challenges and Privacy Concerns Related to Use of Information Technology in Mental Healthcare
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Chapter title
Challenges and Privacy Concerns Related to Use of Information Technology in Mental Healthcare
Chapter number 15
Book title
Predictive Analytics of Psychological Disorders in Healthcare
Published by
Springer, Singapore, January 2022
DOI 10.1007/978-981-19-1724-0_15
Book ISBNs
978-9-81-191723-3, 978-9-81-191724-0
Authors

Siddiqui, Shama, Khan, Anwar Ahmed

Timeline

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 13%
Researcher 2 13%
Student > Bachelor 1 6%
Unspecified 1 6%
Unknown 10 63%
Readers by discipline Count As %
Unspecified 1 6%
Business, Management and Accounting 1 6%
Computer Science 1 6%
Social Sciences 1 6%
Medicine and Dentistry 1 6%
Other 1 6%
Unknown 10 63%