Background: Menstrual health is essential for gender equality and achieving the sustainable development goals.

Figure 4. A systems biology view of the aged breast microenvironment
This Review supports SDGs 3 and 5, focusing on screening, detection, and treatment of oestrogen receptor-positive breast cancers in older women, particularly in relation to recent moves to de-escalate some interventions for this population.
This Article supports SDGs 3 and 5, focusing on blood pressure and hypertension treatment and their association with cognitive impairment and dementia in older women.
Elsevier,

Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications, Volume , 1 January 2022

This content advances goals 4, 5 and 10 by highlighting sex and gender biases in Big Data for biomedicine and healthcare.
This article advances goals 4, 5, and 10 by examining disparities in minority participation in surgical oncology clinical trials.
A Review on the mental health of transgender and gender non-conforming people in China, in the context of SDGs 3 and 5, focusing on the specific actions needed to improve mental health in this population by reducing discrimination and fostering social awareness and acceptance.
This Research Paper supports SDGs 5 and 10 by applying a decision-tree approach to identify subgroups of women at increased risk of IPV across 48 LMICs and to subsequently help design targeted interventions, and by suggesting the need for population-wide approaches in parallel for a large proportion of women with no identifiable risk factors.

Purpose: The purpose of this study was to explore male nurses’ experiences of workplace gender discrimination and sexual harassment in South Korea.

Elsevier,

Journal of Responsible Technology,
Volume 9,
2022,
100020,
ISSN 2666-6596

Concern exists over gender (and other) bias embedded in widely-used AI systems and models. Authors built an open-source tool to help detect bias in classification models: helps to show whether or not AI model is unbiased. Aim to contribute towards action to mitigate the socially harmful effect of machine bias.
Graphical abstract showing how resources depend on income
Low-income households (LIHs) have experienced increased poverty and inaccess to healthcare services during the COVID-19 pandemic, limiting their ability to adhere to health-protective behaviors.

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