This Research Topic is part of the Women in Artificial Intelligence series. Other titles in the series are:
Women in Machine Learning and Artificial Intelligence 2022
Women in Data Mining and Management 2022
Women in Cybersecurity and Privacy
Women in Data-driven Climate Sciences 2022
Women in Recommender Systems
Women in Data Science 2022
Women in Big Data Networks 2022 We are delighted to present the inaugural Frontiers in Artificial Intelligence and Frontiers in Big Data
"Women in AI: Medicine and Public Health” series of article collections.
At present, less than 30% of researchers worldwide are women. Long-standing biases and gender stereotypes are discouraging girls and women away from science-related fields, and STEM research in particular. Science and gender equality are, however, essential to ensure sustainable development as highlighted by UNESCO. In order to change traditional mindsets, gender equality must be promoted, stereotypes defeated, and girls and women should be encouraged to pursue STEM careers.
Therefore, Frontiers in Artificial Intelligence is proud to offer this platform to promote the work of women scientists, across the fields of Medicine and Public Health. This editorial initiative of particular relevance is led by Editors Lin-Ching Chang and Anastassia Angelopoulou. The work presented here highlights the diversity of research performed across the entire breadth of Medicine and Public Health research and presents advances in theory, experiment, and methodology with applications to compelling problems.
Please note: To be considered for this collection, the first or last author should be a researcher who is a woman. This Research Topic is part of the Women in Artificial Intelligence series. Other titles in the series are:
Women in Machine Learning and Artificial Intelligence 2022
Women in Data Mining and Management 2022
Women in Cybersecurity and Privacy
Women in Data-driven Climate Sciences 2022
Women in Recommender Systems
Women in Data Science 2022
Women in Big Data Networks 2022 We are delighted to present the inaugural Frontiers in Artificial Intelligence and Frontiers in Big Data
"Women in AI: Medicine and Public Health” series of article collections.
At present, less than 30% of researchers worldwide are women. Long-standing biases and gender stereotypes are discouraging girls and women away from science-related fields, and STEM research in particular. Science and gender equality are, however, essential to ensure sustainable development as highlighted by UNESCO. In order to change traditional mindsets, gender equality must be promoted, stereotypes defeated, and girls and women should be encouraged to pursue STEM careers.
Therefore, Frontiers in Artificial Intelligence is proud to offer this platform to promote the work of women scientists, across the fields of Medicine and Public Health. This editorial initiative of particular relevance is led by Editors Lin-Ching Chang and Anastassia Angelopoulou. The work presented here highlights the diversity of research performed across the entire breadth of Medicine and Public Health research and presents advances in theory, experiment, and methodology with applications to compelling problems.
Please note: To be considered for this collection, the first or last author should be a researcher who is a woman.