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Sex and Gender Bias in Technology and Artificial Intelligence
Biomedicine and Healthcare Applications
First title addressing the topic of gender biases and artificial intelligence applications to healthcare
Davide Cirillo (Edited by), Silvina Catuara Solarz (Edited by), Emre Guney (Edited by)
9780128213926, Elsevier Science
Hardback, published 27 May 2022
278 pages, Approx. 150 illustrations (150 in full color)
23.5 x 19 x 2.2 cm, 0.77 kg
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. Introducing Women’s Brain Project towards a fair and personalized approach to human health in the era of data-driven medicine Section 1. Sex and gender differences and Precision Medicine 2. Implications of sex-specific differences on clinical studies of human health 3. Sex and gender differences and Precision Medicine Section 2. Biases in innovative technologies for Biomedicine and Health 4. Bias and fairness in machine learning and artificial intelligence 5. Big Data in healthcare from a sex/gender perspective 6. Biases in digital biomarkers and Mobile Health 7. Sex and Gender bias in Natural Language Processing 8. Sex and gender differences in Invasive and non invasive neurotechnologies 9. Robots and Affective technologies Section 3. Towards Precision Technology 10. A unified framework for the management of sex and gender biases in Healthcare 11. Privacy Preserving technologies 12. Ethics and Society
Subject Areas: Neurosciences [PSAN]
