“An engaging study of the ways women and machines have been represented in art, photography, advertising, and literature.” —Arwen Palmer Mohun, University of Delaware From sexist jokes about women drivers to such empowering icons as Amelia Earhart and Rosie the Riveter, representations of the relationship between women and modern technology in popular culture have been both demeaning and celebratory. Depictions of women as timid and fearful creatures baffled by machinery have alternated with images of them as being fully capable of technological mastery and control—and of lending sex appeal to machines as products. In Women and the Machine, historian Julie Wosk maps the contradictory ways in which women’s interactions with—and understanding of—machinery has been defined in Western popular culture since the dawn of the Industrial Revolution. Drawing on both visual and literary sources, Wosk illuminates popular gender stereotypes that have burdened women throughout modern history while underscoring their advances in what was long considered the domain of men. Illustrated with more than 150 images, Women and the Machine reveals women rejoicing in their new liberties and technical skill even as they confront society’s ambivalence about these developments, along with male fantasies and fears. “Engaging and entertaining . . . Using illustrations, cartoons and photographs from the past three centuries, Wosk delineates shifts in social acceptance of women’s relationship to technology . . . her work is complex, comprehensive and highly readable.” —Publishers Weekly “Art historian Wosk analyzes the overt and covert messages in depictions of women and machines in an array of fiction and, more impressively, in some 150 visual images.” —Booklist

Karen Brodine's award-winning feminist poetry explores themes of work, activism, sexual identity, family, language, and the author's fight against breast cancer. Published in 1990, WOMAN SITTING AT THE MACHINE, THINKING is the posthumously published, fourth collection of poems by a breakthrough writer on feminist, lesbian and workingclass themes. Brodine's work is widely published in anthologies. This collection includes a bibliography of Brodine's writing, a preface by the renowned feminist and radical poet Meridel LeSueur, and an introduction by Asian American lesbian poet Merle Woo.

Artificial Intelligence and Machine Learning for Women’s Health Issues: Challenges, Impact, and Solutions discusses the applications, challenges, and solutions that machine learning can bring to women’s health challenges. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning, which enhance the future healthcare system. This book's primary focus is on women’s health issues and machine learning's role in providing solutions to these challenges, providing novel ideas for feasible implementation. It also provides an early-stage analysis for early diagnosis of women’s health issues. Provides fundamental concepts and analysis of machine learning algorithms used to aid in the diagnosis of women’s health issues Guides researchers to specific ideas, tools, and practices most applicable to product/service development, innovation problems, and opportunities Provides hands-on chapters that describe frameworks, applications, best practices, and case studies of future directions of applied machine learning in women’s healthcare

The main focus of this book is the examination of women’s health issues and the role machine learning can play as a solution to these challenges. This book will illustrate advanced, innovative techniques/frameworks/concepts/machine learning methodologies, enhancing the future healthcare system. Combating Women’s Health Issues with Machine Learning: Challenges and Solutions examines the fundamental concepts and analysis of machine learning algorithms. The editors and authors of this book examine new approaches for different age-related medical issues that women face. Topics range from diagnosing diseases such as breast and ovarian cancer to using deep learning in prenatal ultrasound diagnosis. The authors also examine the best machine learning classifier for constructing the most accurate predictive model for women’s infertility risk. Among the topics discussed are gender differences in type 2 diabetes care and its management as it relates to gender using artificial intelligence. The book also discusses advanced techniques for evaluating and managing cardiovascular disease symptoms, which are more common in women but often overlooked or misdiagnosed by many healthcare providers. The book concludes by presenting future considerations and challenges in the field of women’s health using artificial intelligence. This book is intended for medical researchers, healthcare technicians, scientists, programmers and graduate-level students looking to understand better and develop applications of machine learning/deep learning in healthcare scenarios, especially concerning women’s health conditions.