AI and Maternal Health
Chapman & Hall/CRC (Verlag)
978-1-032-95215-4 (ISBN)
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Maternal morbidity in the United States remains alarmingly high, despite rapid medical advancements. The disparities in maternal outcomes - particularly across racial, socioeconomic, and geographic lines - are stark and persistent. This book investigates how artificial intelligence might help reduce these disparities, offering a critical examination of both its potential and its limitations within the evolving maternal health landscape.
This book engages with complex questions about how AI can complement or supplement the work of healthcare providers. It draws on the latest data and research to explore AI’s role across a range of med-tech applications, including chatbots, electronic medical records, virtual coaching, and social media. Through evidence-based analysis, it considers how these technologies might prevent maternal morbidity and mortality, and promote health equity. The book also takes a carefully balanced approach, acknowledging the risks of AI - such as algorithmic bias - and evaluates when and how AI is most or least effective in meeting patient needs.
This is an essential resource for students, researchers, and professionals working in maternal health and related fields. It offers a timely and nuanced perspective on the intersection of technology and care.
Jennifer Schindler-Ruwisch, DrPH, is currently an Associate Professor of Public Health. She is interested in technology that impacts health, like AI, and is especially passionate about maternal-child health. She is active in her community, loves reading, and family game nights. Wes Ruwisch, MBA, is a software engineer with more than a decade of experience in tech. He enjoys music, basketball, and spending time with family.
1. Mhealth before the Dawn of AI
2. Ask the Chatbot
3. Behind the Scenes: The Electronic Medical Record
4. Can AI Triage?
5. Medtech and Risk
6. AI and Big Data
7. AI is Social: Online Information Seeking
8. Enhancing or Reducing Equity-Bias in AI
9. AI's Prevention Power vs. Power: Can we Trust It?
10. AI - Who Pays? Regulations and Insurance
11. Virtual Coaches and Virtual Doctors
12. AI Knows Best?
Conclusion
| Erscheint lt. Verlag | 21.4.2026 |
|---|---|
| Zusatzinfo | 5 Tables, black and white; 6 Halftones, black and white; 6 Illustrations, black and white |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Studium ► Querschnittsbereiche ► Prävention / Gesundheitsförderung | |
| Sozialwissenschaften ► Soziologie | |
| ISBN-10 | 1-032-95215-6 / 1032952156 |
| ISBN-13 | 978-1-032-95215-4 / 9781032952154 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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