Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications

Front Cover
Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications
Copyright
Dedication
Contents
Endorsements
Contributors
Editor Biographies
Acknowledgments
The Women’s Brain Project
1. The birth of the Womens Brain Project
2. The Womens Brain Project way-A holistic approach to a complex topic
3. Becoming an international opinion leader
4. The future: Womens 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 ...
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
3.1. Section 1: Sex and gender differences and precision medicine
3.2. Section 2: Biases in innovative technologies for biomedicine and health
3.3. Section 3: Toward precision technology
Acknowledgments
References
Section 1: Sex and gender differences and precision medicine
Chapter 1: Implications of sex-specific differences on clinical studies of human health
Chapter points
1. Introduction
2. Genetic and physiological differences and differential manifestation of diseases between sexes
2.1. Physiological differences between sexes
2.2. Differential manifestation of diseases across males and females
2.2.1. Immune system disorders
2.2.2. Cardiovascular system disorders
2.2.3. Neurological disorders
2.2.4. Cancer
3. Preclinical and clinical study design: A historical perspective
3.1. Bias toward male models
3.2. Underrepresentation of women in clinical trials
3.3. Differential drug response between sexes
3.4. Toward incorporation of sex and gender information in the study design and analysis
4. Socioeconomic and socioethical considerations
4.1. Cultural and social factors involved in discrepancy
4.2. Interpreting the data toward a fairer clinical trial design
4.3. Initiatives involving underrepresented patient groups
5. Discussion and conclusions
References
Chapter 2: Sex and gender inequality in precision medicine: Socioeconomic determinants of health
Chapter points
1. Introduction
1.1. Better health for all women: A human right concern
2. Precision medicine and inequalities
2.1. Socioeconomic determinants of health
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
Chapter points
1. Introduction
2. A complex landscape of intersecting biases
3. Taxonomies of bias
3.1. Cognitive and statistical biases
3.2. Explicit and implicit biases
3.3. Algorithmic 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
Chapter points
1. Introduction
2. Big Data in healthcare and wellbeing: A sex and gender perspective
2.1. Big Data on healthcare gender-centric initiatives
2.2. Diseases-centered studies
2.3. Knowledge representation
2.4. Fairness
2.5. Deep learning
3. Challenges and opportunities
4. Conclusions
5. Brief summary
References
Chapter 5: Biases in digital health measures
Chapter points
1. Introduction
2. History and development of digital measures
2.1. Recent regulatory advances
3. Biases and their consequences for digital measures
3.1. Origin of biases
3.1.1. Scope of medical assessment
3.1.2. Data generation and evaluation approach
3.1.3. Validation strategy
3.1.4. Framework for the design and deployment at scale
4. Outlook and recommendations
References
Chapter 6: Sex and gender bias in natural language processing
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
Chapter points
1. Introduction
2. Sex differences in noninvasive neurotechnologies
2.1. Noninvasive neurotechnologies for brain monitoring
2.1.1. Electroencephalography (EEG)
2.1.2. Magnetoencephalography (MEG)
2.1.3. Functional near-infrared spectroscopy (fNIRS)
2.2. Noninvasive neurotechnologies for clinical interventions
2.2.1. Transcranial magnetic stimulation
2.2.2. Transcranial direct current stimulation
2.2.3. Neurofeedback
3. Sex differences in invasive neurotechnologies
3.1. Deep brain stimulation (DBS)
3.2. Spinal cord stimulation (SCS)
3.3. Vagal nerve stimulation (VNS)
3.4. Brain computer interfaces (BCI)
4. Ethical considerations
5. Conclusions
References
Chapter 8: How gender is intertwined with robots and affective technologies: A short review
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
Chapter points
1. Introduction
2. A framework to manage sex and gender biases in biomedical research and healthcare
3. Bias identification
3.1. Definition of sex and gender biases in AI models
3.2. Identification of attribute relevance through metrics
4. Bias explanation
4.1. Explainability and bias
4.2. Global explanations
4.3. Local explanations
5. Distinction between desirable and undesirable bias
6. Bias mitigation
6.1. Bias mitigation during data generation phase
6.2. Bias mitigation during algorithm training phase
6.2.1. Adversarial debiasing methods
6.2.2. Correction of undesirable bias: A case study
6.2.3. Other debiasing methods
7. Bias exploitation: Use of desirable bias for precision medicine
7.1. Patient stratification based on sex or gender
7.2. Causal inference of sex and gender on health parameters
7.3. Disease predictions based on sex/gender
7.4. Recommendations based on sex and/or gender
8. Summary and conclusions
References
Chapter 10: Privacy issues in healthcare and their mitigation through privacy preserving technologies
Chapter points
1. Introduction
1.1. Balancing private and public interest
2. Responsible use of data and AI in healthcare
2.1. Global emergence of AI principles
2.2. Deployment of AI in the medical sector
3. Embedding privacy in AI
3.1. Privacy implications of gender focused AI in healthcare
4. Epilogue
5. Conclusion
References
Chapter 11: Societal and ethical impact of technologies for health and biomedicine
Chapter points
1. Introduction
1.1. A new paradigm of sex and gender inclusive healthcare ecosystem
1.2. The digital divide in digital health
2. An ethical framework for AI in healthcare and biomedicine
2.1. Bioethical principles
2.2. Ethical principles for AI
2.3. AI for social good
2.4. Responsible AI in healthcare
3. Conclusions
References
Conclusion: Toward sex- and gender-stratified precision medicine
Index
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