LSTM Autoencoder-Based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction DOI
Guanjin Wang, Junyu Xuan, Penghao Wang

et al.

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 342 - 353

Published: Nov. 18, 2024

Language: Английский

Interactive Conversational Agents for Perinatal Health: A Mixed Methods Systematic Review DOI Open Access
Samira Amil, Sié-Mathieu-Aymar-Romaric Da, James Plaisimond

et al.

Healthcare, Journal Year: 2025, Volume and Issue: 13(4), P. 363 - 363

Published: Feb. 8, 2025

Background: Interactive conversational agents (chatbots) simulate human conversation using natural language processing and artificial intelligence. They enable dynamic interactions are used in various fields, including education healthcare. Objective: This systematic review aims to identify synthesize studies on chatbots for women expectant parents the preconception, pregnancy, postnatal period through 12 months postpartum. Methods: We searched six electronic bibliographic databases (MEDLINE (Ovid), CINAHL (EBSCO), Embase, Web of Science, Inspec, IEEE Xplore) a pre-defined search strategy. included sources if they focused preconception period, pregnant their partners, mothers, fathers/coparents babies up old. Two reviewers independently screened all disagreements were resolved by third reviewer. extracted validated data from into standardized form conducted quality appraisal. Results: Twelve met inclusion criteria. Seven USA, with others Brazil, South Korea, Singapore, Japan. The reported high user satisfaction, improved health intentions behaviors, increased knowledge, better prevention risks. Chatbots also facilitated access information professionals. Conclusion: provide an overview interactive perinatal applications. Digital interventions have positive impact attitudes, use services. Interventions may be more effective than those methods such as individual or group face-to-face delivery.

Language: Английский

Citations

1

Revolutionizing Maternal Health: The Role of Artificial Intelligence in Enhancing Care and Accessibility DOI Open Access

Smruti A Mapari,

Deepti Shrivastava,

Apoorva Dave

et al.

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 16, 2024

Maternal health remains a critical global challenge, with disparities in access to care and quality of services contributing high maternal mortality morbidity rates. Artificial intelligence (AI) has emerged as promising tool for addressing these challenges by enhancing diagnostic accuracy, improving patient monitoring, expanding care. This review explores the transformative role AI healthcare, focusing on its applications early detection pregnancy complications, personalized care, remote monitoring through AI-driven technologies. tools such predictive analytics machine learning can help identify at-risk pregnancies guide timely interventions, reducing preventable neonatal complications. Additionally, AI-enabled telemedicine virtual assistants are bridging healthcare gaps, particularly underserved rural areas, accessibility women who might otherwise face barriers Despite potential benefits, data privacy, algorithmic bias, need human oversight must be carefully addressed. The also discusses future research directions, including globally ethical frameworks integration. holds revolutionize both accessibility, offering pathway safer, more equitable outcomes.

Language: Английский

Citations

5

A scoping review of effective health practices for the treatment of birth trauma DOI Creative Commons
Julie Jomeen,

Frances Guy,

Julia Marsden

et al.

Midwifery, Journal Year: 2025, Volume and Issue: unknown, P. 104382 - 104382

Published: March 1, 2025

Language: Английский

Citations

0

The role of artificial intelligence in the prediction, identification, diagnosis and treatment of perinatal depression and anxiety among women in LMICs: a systematic review protocol DOI Creative Commons

Uchechi Shirley Anaduaka,

Ayomide Oluwaseyi Oladosu,

Samantha Katsande

et al.

BMJ Open, Journal Year: 2025, Volume and Issue: 15(4), P. e091531 - e091531

Published: April 1, 2025

Introduction Perinatal depression and anxiety (PDA) is associated with a high risk of maternal mortality. Existing data shows that 95% mortality in low- middle-income countries (LMICs) due to resource constraints negligence addressing perinatal mental health (PMH). Research conducted more developed has demonstrated the potential artificial intelligence (AI) assist predicting, identifying, diagnosing treating PDA. However, there limited knowledge regarding utilisation AI LMICs where PDA disproportionately affects women. Therefore, this study aims investigate role among pregnant women mothers LMICs. Methods analysis This systematic review will use patient public involvement (PPI) approach systematically diagnosing, The combine secondary evidence from academic databases primary focus group discussions workshop webinar comprehensively analyse all relevant published reported on period between January 2010 May 2024. To gather necessary data, reputable interdisciplinary field be used, including ACM Digital Library, CINAHL, MEDLINE, PsycINFO, Scopus Web Science. extracted following Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA) framework, ensuring transparency comprehensiveness reporting findings. Finally, studies synthesised using integrative synthesis approach. Ethics dissemination Given PPI employed by which involves multi-stakeholders lived experience, ethical approvals have been sought University Ghana Alberta. Additionally, during process, ensure articles included uphold standards, only peer-reviewed journals/databases review. findings disseminated through workshops, webinars, conferences, publications, social media platforms available researchers. PROSPERO registration number (10/06/24) CRD42024549455.

Language: Английский

Citations

0

Current Applications of Artificial Intelligence in Reproductive Medicine (and Predominant OB/GYN and Andrologic Conditions) DOI
Nicholas A Kerna, Taylor M. Nicely, Kingsley Chigozie Iheanacho

et al.

European Journal of Theoretical and Applied Sciences, Journal Year: 2025, Volume and Issue: 3(3), P. 110 - 122

Published: April 28, 2025

Artificial intelligence (AI) has increasingly permeated clinical domains, including reproductive medicine, where its applications span from gamete assessment to population-level epidemiology. The convergence of machine learning, deep natural language processing, and computer vision enabled novel diagnostic, predictive, decision-support tools that enhance efficiency patient outcomes. This paper provides a review current AI technologies in encompassing assisted technologies, prenatal care, maternal health, sexual contraceptive epidemiology, low-resource settings. Ethical, legal, social implications, as well challenges related data quality, validation, integration, are explored. Future opportunities explainable AI, precision medicine real-world evidence generation, global collaboration discussed. analysis underscores AI’s transformative potential highlights pathways for responsible deployment advance medicine.

Language: Английский

Citations

0

Screening Social Anxiety with the Social Artificial Intelligence Picture System DOI
Qianqian Ju,

Zhijian Xu,

Z C Chen

et al.

Journal of Anxiety Disorders, Journal Year: 2024, Volume and Issue: 109, P. 102955 - 102955

Published: Dec. 6, 2024

Language: Английский

Citations

1

LSTM Autoencoder-Based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction DOI
Guanjin Wang, Junyu Xuan, Penghao Wang

et al.

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 342 - 353

Published: Nov. 18, 2024

Language: Английский

Citations

0