This content aligns with Goal 3: Good Health and Wellbeing as well as Goal 10: Reduced Inequalities by emphasizing the importance of technology assessment capability in shaping health policy and priorities to improve health outcomes and quality of life. By promoting strong professional education and practice standards, accreditation processes, and educational programs for public health, the content supports efforts to enhance the quality of healthcare services and public health interventions. Additionally, it aligns with Goal 10: Reduced Inequalities by recognizing the need to address disparities and ensure equitable access to evidence-based methods of prevention, diagnosis, and therapy. By advocating for continuous revision of legal frameworks and ethical standards in response to societal changes and emerging health challenges, the content underscores the importance of promoting fairness and equity in public health practices and policies. Moreover, it highlights the ethical imperative of public health interventions to protect populations from illness and premature death, thereby contributing to efforts aimed at reducing inequalities in health outcomes and promoting the well-being of all members of society.
We observe the link between Artificial Intelligence (AI) and Sustainable Development Goals (SDGs). We use automated methodologies to find insights and overlaps between AI and the SDGs. AI-Ethics frameworks need to give more attention to Society and Environment areas. Inclusive action is needed to balance the efforts for solving SDGs by using AI.SDGs 13, 14, and 15 (all related to the Environment area) are not sufficiently addressed.
Study built over two decades of research on intimate parther violence and HIV. Sub-Saharan Africa has among the highest prevalence of intimate parthner violence (IPV) and HIV worldwide. The results of this very pooled analysis show that pwomen who had experienced physical or sexual IPV in the past year were 3·22 times as likely to acquire a recent HIV infection and women living with HIV who experienced physical or sexual IPV in the past year were 9% less likely to be virally suppressed
The study aims to investigate whether machine learning-based predictive models for cardiovascular disease (CVD) risk assessment show equivalent performance across demographic groups (such as race and gender) and if bias mitigation methods can reduce any bias present in the models. This is important as systematic bias may be introduced when collecting and preprocessing health data, which could affect the performance of the models on certain demographic sub-cohorts.
This chapter advances Goals 5 and 10 by addressing ways we can support the needs of female hand surgeons.
This content advances goals 4, 5 and 10 by highlighting diversity, equity and inclusion for women in the world of hand surgery.
This review article advances goals 3, 5, and 10 by addressing inequity in care among pregnant women with asthma in underserved communities and examining potential interventions that may help improve health outcomes and standard of care.
This content aligns with Goal 5: Gender Equality and Goal 9: Industry, Innovation, and Infrastructure by considering cyber crime emergence, detection, and the populations that may be most affected.
THis supports SGDs 3 and 5 by supporting access to care and contraception.
Good access to care and contraception support SDG 3.
