Background/Objectives: Adverse pregnancy outcomes (APOs), which include hypertensive disorders of pregnancy (gestational hypertension, preeclampsia, and related disorders), gestational diabetes, preterm birth, fetal growth restriction, low birth weight, small-for-gestational-age newborn, placental abruption, and stillbirth, are health risks for pregnant women that can have fatal outcomes. This study’s aim is to investigate the usefulness of artificial intelligence (AI) in improving these outcomes and includes changes in the utilization of ultrasound, continuous monitoring, and an earlier prediction of complications, as well as being able to individualize processes and support clinical decision-making. This study evaluates the use of AI in improving at least one APO. Methods: PubMed, Web of Science, and Scopus databases were searched and limited to the English language, humans, and between 2020 and 2024. This scoping review included peer-reviewed articles across any study design. However, systematic reviews, meta-analyses, unpublished studies, and grey literature sources (e.g., reports and conference abstracts) were excluded. Studies were eligible for inclusion if they described the use of AI in improving APOs and the associated ethical issues. Results: Five studies met the inclusion criteria and were included in this scoping review. Although this review initially aimed to evaluate AI’s role across a wide range of APOs, including placental abruption and stillbirth, the five selected studies focused primarily on preterm birth, hypertensive disorders of pregnancy, and gestational diabetes. None of the included studies addressed placental abruption or stillbirth directly. The studies primarily utilized machine-learning models, including extreme gradient boosting (XGBoost) and random forest (RF), showing promising results in enhancing prenatal care and supporting clinical decision-making. Ethical considerations, including algorithmic bias, transparency, and the need for regulatory oversight, were highlighted as critical challenges. Conclusions: The application of these tools can improve prenatal care by predicting obstetric complications, but ethics and transparency are pivotal. Empathy and humanization in healthcare must remain fundamental, and flexible training mechanisms are needed to keep up with rapid innovation. AI offers an opportunity to support, not replace, the doctor–patient relationship and must be subject to strict legislation if it is to be used safely and fairly.

International studies indicate that Chinese immigrants face barriers when trying to access healthcare in the host country. The aim of this study was to identify the barriers that Chinese immigrants face when accessing the Portuguese National Health Service. An observational, cross-sectional and quantitative study was carried out via a bilingual Portuguese/Mandarin self-completed paper questionnaire was applied. The study population consisted of individuals with Chinese nationality who were residing in mainland Portugal for at least one year and aged 18 years or over. A total of 304 individuals answered the questionnaire. The results show that 284 (93.4%) of the participants had already sought healthcare in Portugal. The participants identified language difficulties and health professionals’ lack of knowledge of Chinese cultural habits as the most significant barriers to accessing healthcare in Portugal. Of a total of 165 participants who sought healthcare in China, confidence in treatment outcomes and health professionals’ knowledge of Chinese cultural habits were the reasons given by 151 (91.5%) individuals. This study reveals the existence of linguistic and cultural barriers that can condition the access of the Chinese immigrant population to healthcare systems. Immigrants’ access to healthcare can be promoted via policies that contribute to proficiency in the Portuguese language and medical literacy among the Chinese immigrant population. It can also be promoted by raising the awareness of health professionals to Chinese cultural habits.

Background/Objectives: Unequal access to cervical cancer screening and treatment remains a significant contributor to preventable morbidity and mortality for women in the Amazon Basin, compounded by geographic, social and infrastructural barriers. Given the fragmented nature of the existing evidence, this systematic review aims to synthesize available findings on barriers to cervical cancer screening and treatment for this region. The implications of these findings are examined to inform the development of actionable strategies to improve equity in prevention and care. Methods: This systematic review was conducted in accordance with PRISMA 2020. Searches were conducted on 7 November 2025, in PubMed/MEDLINE, Web of Science, and SciELO, utilizing combinations of MeSH terms, keywords, and free-text expressions. Studies were considered eligible if they addressed barriers to cervical cancer screening or treatment among women living in the Amazon Region. Two reviewers independently screened the studies and extracted the relevant data. The risk of bias was assessed using the JBI checklists, the Newcastle–Ottawa Scale, and the MMAT. A narrative synthesis summarized the results. Results: Of 57 studies identified, 11 were included. Organizational and health-system barriers were reported most frequently, including scheduling difficulties, long wait times, a shortage of professionals, and equipment unavailability. Socioeconomic barriers were most often related to younger age, low income, limited schooling, and care related expenses. Cultural factors were frequently linked to fear of the procedure and insufficient knowledge about cervical cancer. Geographic barriers included rural residence and travel difficulties. Conclusions: This systematic review indicates that disparities in cervical cancer screening in the Amazon region are primarily associated with organizational and health-system-related barriers, together with socioeconomic, cultural, and geographic factors. These findings highlight the need for equitable, multisectoral interventions to strengthen service organization, improve health literacy, and expand timely access to screening and treatment for underserved women.

INPLASY202520065 Artificial Intelligence in Improving Adverse Pregnancy Outcomes – A Scoping Review and Ethical Issues Keywords: Artificial intelligence, perinatal care, pregnancy outcome, ethics. …