Sex 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.
1. Chapter 0 : Introduction: The relevance of sex and gender in precision medicine and the role of technologies and artificial intelligence - p. Page xv 2. Chapter 1 : Implications of sex-specific differences on clinical studies of human health - p. Page 7 3. Chapter 2 : Sex and gender inequality in precision medicine: Socioeconomic determinants of health - p. Page 26 4. Chapter 3 : Bias and fairness in machine learning and artificial intelligence - p. Page 50 5. Chapter 4 : Big Data in healthcare from a sex and gender perspective - p. Page 72 6. Chapter 5 : Biases in digital health measures - p. Page 91 7. Chapter 6 : Sex and gender bias in natural language processing - p. Page 109 8. Chapter 7 : Sex differences in invasive and noninvasive neurotechnologies - p. Page 126 9. Chapter 8 : How gender is intertwined with robots and affective technologies: A short review - p. Page 154 10. Chapter 9 : A unified framework for managing sex and gender bias in AI models for healthcare - p. Page 172 11. Chapter 10 : Privacy issues in healthcare and their mitigation through privacy preserving technologies - p. Page 202 12. Chapter 11 : Societal and ethical impact of technologies for health and biomedicine - p. Page 217 13. Conclusion: Toward sex- and gender-stratified precision medicine - p. Page 236 14. Index - p. Page 241
Sex 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.
1. Chapter 0 : Introduction: The relevance of sex and gender in precision medicine and the role of technologies and artificial intelligence - p. Page xv 2. Chapter 1 : Implications of sex-specific differences on clinical studies of human health - p. Page 7 3. Chapter 2 : Sex and gender inequality in precision medicine: Socioeconomic determinants of health - p. Page 26 4. Chapter 3 : Bias and fairness in machine learning and artificial intelligence - p. Page 50 5. Chapter 4 : Big Data in healthcare from a sex and gender perspective - p. Page 72 6. Chapter 5 : Biases in digital health measures - p. Page 91 7. Chapter 6 : Sex and gender bias in natural language processing - p. Page 109 8. Chapter 7 : Sex differences in invasive and noninvasive neurotechnologies - p. Page 126 9. Chapter 8 : How gender is intertwined with robots and affective technologies: A short review - p. Page 154 10. Chapter 9 : A unified framework for managing sex and gender bias in AI models for healthcare - p. Page 172 11. Chapter 10 : Privacy issues in healthcare and their mitigation through privacy preserving technologies - p. Page 202 12. Chapter 11 : Societal and ethical impact of technologies for health and biomedicine - p. Page 217 13. Conclusion: Toward sex- and gender-stratified precision medicine - p. Page 236 14. Index - p. Page 241
