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  • Book
  • © 2022

AI for Disease Surveillance and Pandemic Intelligence

Intelligent Disease Detection in Action

  • Highlights latest achievements in the use of artificial intelligence for disease surveillance, pandemic intelligence

  • Interconnects three major fields: Artificial intelligence, Medicine and clinical and public health informatics

  • Makes the emerging topics of digital health and AI in medicine accessible to a broad readership

Part of the book series: Studies in Computational Intelligence (SCI, volume 1013)

Conference series link(s): W3PHAI: International Workshop on Health Intelligence

Conference proceedings info: W3PHAI 2021.

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-93080-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 169.99
Price excludes VAT (USA)
Hardcover Book USD 169.99
Price excludes VAT (USA)

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Table of contents (23 chapters)

  1. Front Matter

    Pages i-xix
  2. Digital Technologies for Clinical, Public and Global Health Surveillance

    • Arash Shaban-Nejad, Martin Michalowski, Simone Bianco
    Pages 1-9
  3. Lexical and Acoustic Correlates of Clinical Speech Disturbance in Schizophrenia

    • Rony Krell, Wenqing Tang, Katrin Hänsel, Michael Sobolev, Sunghye Cho, Sarah Berretta et al.
    Pages 27-35
  4. A Prognostic Tool to Identify Youth at Risk of at Least Weekly Cannabis Use

    • Marie-Pierre Sylvestre, Simon de Montigny, Laurence Boulanger, Danick Goulet, Isabelle Doré, Jennifer O’Loughlin et al.
    Pages 37-48
  5. Identifying Prepubertal Children with Risk for Suicide Using Deep Neural Network Trained on Multimodal Brain Imaging

    • Gun Ahn, Bogyeom Kim, Ka-kyeong Kim, Hyeonjin Kim, Eunji Lee, Woo-Young Ahn et al.
    Pages 75-86
  6. Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies

    • Beatrice Portelli, Daniele Passabì, Edoardo Lenzi, Giuseppe Serra, Enrico Santus, Emmanuele Chersoni
    Pages 87-99
  7. Machine Learning Identification of Self-reported COVID-19 Symptoms from Tweets in Canada

    • Jean-Philippe Gilbert, Jingcheng Niu, Simon de Montigny, Victoria Ng, Erin Rees
    Pages 101-111
  8. RRISK: Analyzing COVID-19 Risk in Food Establishments

    • Saahil Sundaresan, Shafin Khan, Faraz Rahman, Chris Huang
    Pages 113-129
  9. AWS CORD-19 Search: A Neural Search Engine for COVID-19 Literature

    • Parminder Bhatia, Lan Liu, Kristjan Arumae, Nima Pourdamghani, Suyog Deshpande, Ben Snively et al.
    Pages 131-145
  10. Inferring COVID-19 Biological Pathways from Clinical Phenotypes Via Topological Analysis

    • Negin Karisani, Daniel E. Platt, Saugata Basu, Laxmi Parida
    Pages 147-163
  11. Interpretable Classification of Human Exercise Videos Through Pose Estimation and Multivariate Time Series Analysis

    • Ashish Singh, Binh Thanh Le, Thach Le Nguyen, Darragh Whelan, Martin O’Reilly, Brian Caulfield et al.
    Pages 181-199
  12. Interpreting Deep Neural Networks for Medical Imaging Using Concept Graphs

    • Avinash Kori, Parth Natekar, Balaji Srinivasan, Ganapathy Krishnamurthi
    Pages 201-216
  13. Utilizing Predictive Analysis to Aid Emergency Medical Services

    • Pratyush Kumar Sahoo, Nidhi Malhotra, Shirley Sanjay Kokane, Biplav Srivastava, Harsh Narayan Tiwari, Sushant Sawant
    Pages 235-245
  14. Measuring Physiological Markers of Stress During Conversational Agent Interactions

    • Shreya Datar, Libby Ferland, Esther Foo, Michael Kotlyar, Brad Holschuh, Maria Gini et al.
    Pages 247-265
  15. EvSys: A Relational Dynamic System for Sparse Irregular Clinical Events

    • Duc Nguyen, Phuoc Nguyen, Truyen Tran
    Pages 267-279

About this book

This book aims to highlight the latest achievements in the use of artificial intelligence for digital disease surveillance, pandemic intelligence, as well as public and clinical health surveillance. The edited book contains selected papers presented at the 2021 Health Intelligence workshop, co-located with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. While disease surveillance has always been a crucial process, the recent global health crisis caused by COVID-19 has once again highlighted our dependence on intelligent surveillance infrastructures that provide support for making sound and timely decisions. This book provides information for researchers, students, industry professionals, and public health agencies interested in the applications of AI in population health and personalized medicine.

Keywords

  • Health Intelligence
  • Precession Medicine
  • Precession Health
  • Digital Medicine
  • Big Data
  • Predictive Analytics
  • Clinical Intelligence
  • Public Health Surveillance
  • Medical Informatics
  • Health Informatics
  • W3PHIAI
  • W3PHIAI2021

Editors and Affiliations

  • Oak-Ridge National Lab (ORNL), Department of Pediatrics, Center for Biomedical Informatics, College of Medicine, The University of Tennessee Health Science Center (UTHSC), Memphis, USA

    Arash Shaban-Nejad

  • School of Nursing, University of Minnesota, Minneapolis, USA

    Martin Michalowski

  • IBM Almaden Research Center, San Jos, USA

    Simone Bianco

Bibliographic Information

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-93080-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 169.99
Price excludes VAT (USA)
Hardcover Book USD 169.99
Price excludes VAT (USA)