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.
Key Features
- 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
Introduction
Silvina Catuara-Solarz, Davide Cirillo, Emre Guney
1. The Women’s Brain Project
Maria Teresa Ferretti, Antonella Santuccione Chadha and Simona Mellino
Section 1. Sex and gender differences and Precision Medicine
2. Implications of sex-specific differences on clinical studies of human health
Janet Piñero, Frances-Catherine Quevenco, Laura Furlong and Emre Guney
3. Socio-economic factors
Nataly Buslón, Sandra Racionero and Àtia Cortés
Section 2. Biases in innovative technologies for Biomedicine and Health
4. Bias and fairness in machine learning and artificial intelligence
Davide Cirillo and María José Rementeria
5. Big Data in healthcare from a sex/gender perspective
Laia Subirats and Gemma Piella
6. Biases in digital biomarkers and Mobile Health
Simona Mellino, Czuee Morey and Colin Rohner
7. Sex and Gender bias in Natural Language Processing
Davide Cirillo, Hila Gonen, Enrico Santus, Alfonso Valencia, Marta R. Costa-jussà and Marta Villegas
8. Sex and gender differences in Invasive and non invasive neurotechnologies
Laura Dubreuil Vall, Tracy Laabs, Harris Eyre, Erin Smith and Silvina Catuara Solarz
9. Robots and Affective technologies
Nikolaos Mavridis
Section 3. Towards Precision Technology
10. A unified framework for managing sex and gender bias in AI models for Healthcare
Roberto Confalonieri, Federico Lucchesi, Giovanni Maffei and Silvina Catuara Solarz
11. Privacy Preserving AI
Ladina Caduff, Gianluca Diana, Cornelia Kutterer and Spyridon Papasotiriou
12. Ethics and Society (Societal and Ethical Impact of technologies for Health and Biomedicine)
Àtia Cortés, Liliana Arroyo and Nataly Buslón
13. Conclusion
Emre Guney, Davide Cirillo, Silvina Catuara-Solarz
9780123919243; 9780124202481; 9780128021149
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
