Proportion of pregnant women with HBV infection eligible for antiviral prophylaxis to prevent vertical transmission: A systematic review and meta-analysis.

Background & Aims: In 2020, the World Health Organization (WHO) recommended peripartum antiviral prophylaxis (PAP) for pregnant women infected with hepatitis B virus (HBV) with high viremia (≥200,000 IU/ml). Hepatitis B e antigen (HBeAg) was also recommended as an alternative when HBV DNA is unavailable. To inform policymaking and guide the implementation of prevention of mother-to-child transmission strategies, we conducted a systematic review and meta-analysis to estimate the proportion of HBV-infected pregnant women eligible for PAP at global and regional levels.

The "Ecosystem as a Service (EaaS)" approach to advance clinical artificial intelligence (cAI).

The application of machine learning and artificial intelligence to clinical settings for prevention, diagnosis, treatment, and the improvement of clinical care have been demonstrably cost-effective. However, current clinical AI (cAI) support tools are predominantly created by non-domain experts and algorithms available in the market have been criticized for the lack of transparency behind their creation. To combat these challenges, the Massachusetts Institute of Technology Critical Data (MIT-CD) consortium, an affiliation of research labs, organizations, and individuals that contribute to research in and around data that has a critical impact on human health, has iteratively developed the "Ecosystem as a Service (EaaS)" approach, providing a transparent education and accountability platform for clinical and technical experts to collaborate and advance cAI.