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Sex and Gender Bias in Technology and Artificial Intelligence
Biomedicine and Healthcare Applications
- 1st Edition - May 21, 2022
- Editors: Davide Cirillo, Silvina Catuara Solarz, Emre Guney
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 8 2 1 3 9 2 - 6
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 1 3 9 3 - 3
Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovativ… Read more
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Request a sales quoteSex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovative technologies (artificial intelligence, digital medicine, natural language processing, robotics) for biomedicine and healthcare applications. By systematically reviewing existing scientific literature, a multidisciplinary group of international experts analyze diverse aspects of the complex relationship between sex and gender, health and technology, providing a perspective overview of the pressing need of an ethically-informed science. The reader is guided through the latest implementations and insights in technological areas of accelerated growth, putting forward the neglected and overlooked aspects of sex and gender in biomedical research and healthcare solutions that leverage artificial intelligence, biosensors, and personalized medicine approaches to predict and prevent disease outcomes. The reader comes away with a critical understanding of this fundamental issue for the sake of better future technologies and more effective clinical approaches.
- First comprehensive title addressing the topic of sex and gender biases and artificial intelligence applications to biomedical research and healthcare
- Co-published by the Women’s Brain Project, a leading non-profit organization in this area
- Guides the reader through important topics like the Generation of Clinical Data, Clinical Trials, Big Data Analytics, Digital Biomarkers, Natural Language Processing
Researchers, advanced graduate students, bioengineers, digital therapeutic product developers, and clinicians in the fields of neuroscience, psychiatry, biomedicine, and computer science. Regulators and policy makers
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Endorsements
- Contributors
- Editor Biographies
- Acknowledgments
- The Women’s Brain Project
- 1: The birth of the Women’s Brain Project
- 2: The Women’s Brain Project way—A holistic approach to a complex topic
- 3: Becoming an international opinion leader
- 4: The future: Women’s Brain Project call to action
- References
- Chapter 0: Introduction: The relevance of sex and gender in precision medicine and the role of technologies and artificial intelligence
- 1: Sex and gender in biomedical research and medicine
- 2: The role of technologies and AI to understand sex and gender differences in health
- 3: Organization and scope of this book
- Acknowledgments
- References
- Section 1: Sex and gender differences and precision medicine
- Chapter 1: Implications of sex-specific differences on clinical studies of human health
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: Genetic and physiological differences and differential manifestation of diseases between sexes
- 3: Preclinical and clinical study design: A historical perspective
- 4: Socioeconomic and socioethical considerations
- 5: Discussion and conclusions
- References
- Chapter 2: Sex and gender inequality in precision medicine: Socioeconomic determinants of health
- Abstract
- Chapter points
- 1: Introduction
- 2: Precision medicine and inequalities
- 3: Future directions
- References
- Section 2: Biases in innovative technologies for biomedicine and health
- Chapter 3: Bias and fairness in machine learning and artificial intelligence
- Abstract
- Acknowledgments
- 1: Introduction
- 2: A complex landscape of intersecting biases
- 3: Taxonomies of bias
- 4: From ideation to deployment: The life cycle of AI development
- 5: Bias metrics
- 6: Conclusions
- References
- Chapter 4: Big Data in healthcare from a sex and gender perspective
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: Big Data in healthcare and wellbeing: A sex and gender perspective
- 3: Challenges and opportunities
- 4: Conclusions
- 5: Brief summary
- References
- Chapter 5: Biases in digital health measures
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: History and development of digital measures
- 3: Biases and their consequences for digital measures
- 4: Outlook and recommendations
- References
- Chapter 6: Sex and gender bias in natural language processing
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: NLP today: Breakthroughs and new challenges
- 3: NLP for biomedicine and health
- 4: A case in study: Chatbots for mental health
- 5: Sex and gender bias in the training corpora
- 6: Debiasing methods
- 7: Discussion
- References
- Chapter 7: Sex differences in invasive and noninvasive neurotechnologies
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: Sex differences in noninvasive neurotechnologies
- 3: Sex differences in invasive neurotechnologies
- 4: Ethical considerations
- 5: Conclusions
- References
- Chapter 8: How gender is intertwined with robots and affective technologies: A short review
- Abstract
- Chapter points
- 1: Introduction
- 2: Robots
- 3: Robots for healthcare and wellbeing
- 4: Sex and gender aspects
- 5: Affective technologies
- 6: Discussion/conclusion
- References
- Section 3: Toward precision technology
- Chapter 9: A unified framework for managing sex and gender bias in AI models for healthcare
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: A framework to manage sex and gender biases in biomedical research and healthcare
- 3: Bias identification
- 4: Bias explanation
- 5: Distinction between desirable and undesirable bias
- 6: Bias mitigation
- 7: Bias exploitation: Use of desirable bias for precision medicine
- 8: Summary and conclusions
- References
- Chapter 10: Privacy issues in healthcare and their mitigation through privacy preserving technologies
- Abstract
- Acknowledgments
- Chapter points
- 1: Introduction
- 2: Responsible use of data and AI in healthcare
- 3: Embedding privacy in AI
- 4: Epilogue
- 5: Conclusion
- References
- Chapter 11: Societal and ethical impact of technologies for health and biomedicine
- Abstract
- Chapter points
- 1: Introduction
- 2: An ethical framework for AI in healthcare and biomedicine
- 3: Conclusions
- References
- Conclusion: Toward sex- and gender-stratified precision medicine
- Index
- No. of pages: 278
- Language: English
- Edition: 1
- Published: May 21, 2022
- Imprint: Academic Press
- Hardback ISBN: 9780128213926
- eBook ISBN: 9780128213933
DC
Davide Cirillo
Davide Cirillo, Ph.D. is a postdoctoral researcher at Barcelona Supercomputing Center
(BSC) Computational Biology group, Life Sciences Department. Davide Cirillo received
the MSc degree in Pharmaceutical Biotechnology from University of Roma ‘La
Sapienza’, Italy, and the PhD degree in Biomedicine from Universitat Pompeu Fabra
(UPF) and Center for Genomic Regulation (CRG) of Barcelona, Spain. His research is
devoted to the development and application of computational methods in Precision
Medicine with a special emphasis on Machine Learning and Artificial Intelligence.
Affiliations and expertise
Postdoctoral Researcher, Barcelona Supercomputing Center (BSC) Computational
Biology Group, Life Sciences Department, SpainSC
Silvina Catuara Solarz
Silvina Catuara-Solarz, Ph.D. is a translational neuroscientist with expertise in
neurodevelopmental, neurodegenerative and psychiatric disorders. After earning a
Ph.D. in Biomedicine by the Pompeu Fabra University that she developed at the Centre
for Genomic Regulation (CRG), the Hospital del Mar Research Institute (IMIM)
(Barcelona, Spain) and the University of California Irvine (Irvine, United States), she
worked on target identification for drug development at Janssen Pharmaceutica
(Beerse, Belgium). Driven by her interests in merging Technology and Health, she then
joined the Health Moonshot at Telefonica Innovation Alpha (Barcelona, Spain) as
Strategy Manager where she was involved with the development of evidence-based
digital mental health solutions and their efficacy assessment.
Given her conviction in the importance of sex and gender for the progress of medicine,
Dr. Catuara-Solarz is an active member of the Women’s Brain Project. She has a track
record of high impact scientific publications as well as books for the lay audience.
Currently Dr. Catuara-Solarz is a selected member of the World Health Organisation
Digital Health Roster of Experts and she serves in the European Institute of
Innovation and Technology Health (EIT Health) as a project evaluator and a mentor of
start-ups in the digital health and medtech sector.
Affiliations and expertise
Women’s Brain Project (WBP), World Health Organisation (WHO), European Institute
of Innovation and Technology Health (EIT Health)EG
Emre Guney
Emre Guney, Ph.D. is a Senior Research Fellow at the Research Programme on Biomedical Informatics (GRIB), at the Pompeu Fabra University (UPF) and Hospital del Mar Research Institute (IMIM) in Barcelona, Spain and works on developing computational systems biology models for network medicine. He holds a secondary appointment at the Pharmacology & Personalised Medicine department at Maastricht University in the Netherlands. He obtained a B.S. in Computer Engineering from Middle East Technical University (METU), Ph.D. in Biomedicine from Pompeu Fabra University (UPF) and spent several years as a postdoctoral scholar at the Center for Complex Network Research (CCNR) and the Center for Cancer Systems Biology (CCSB), Boston, MA, USA.
Affiliations and expertise
Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research; Institute (IMIM) and Pompeu Fabra University (UPF), Barcelona, Spain; Pharmacology and Personalised Medicine department, Maastricht University, Maastricht, The NetherlandsRead Sex and Gender Bias in Technology and Artificial Intelligence on ScienceDirect