Sex and Gender Bias in Technology and Artificial Intelligence

Biomedicine and Healthcare Applications
Herausgeber: Cirillo, Davide; Guney, Emre; Catuara Solarz, Silvina

• Gebundenes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Elsevier Science Publishing Co Inc
• Seitenzahl: 278
• Erscheinungstermin: 27. Mai 2022
• Englisch
• Abmessung: 239mm x 191mm x 20mm
• Gewicht: 744g
• ISBN-13: 9780128213926
• ISBN-10: 0128213922
• Artikelnr.: 60980318

Inhaltsangabe

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