| Autor: |
Periáñez Á; Causal Foundry, Inc, Newark, DE, USA., Fernández Del Río A; Causal Foundry, Inc, Newark, DE, USA., Nazarov I; Causal Foundry, Inc, Newark, DE, USA., Jané E; Causal Foundry, Inc, Newark, DE, USA., Hassan M; Causal Foundry, Inc, Newark, DE, USA., Rastogi A; Causal Foundry, Inc, Newark, DE, USA., Tang D; Causal Foundry, Inc, Newark, DE, USA. |
| Abstrakt: |
Mobile health has the potential to revolutionize health care delivery and patient engagement. In this work, we discuss how integrating Artificial Intelligence into digital health applications focused on supply chain operation, patient management, and capacity building, among other use cases, can improve the health system and public health performance. We present the Causal Foundry Artificial Intelligence and Reinforcement Learning platform, which allows the delivery of adaptive interventions whose impact can be optimized through experimentation and real-time monitoring. The system can integrate multiple data sources and digital health applications. The flexibility of this platform to connect to various mobile health applications and digital devices, and to send personalized recommendations based on past data and predictions, can significantly improve the impact of digital tools on health system outcomes. The potential for resource-poor settings, where the impact of this approach on health outcomes could be decisive, is discussed. This framework is similarly applicable to improving efficiency in health systems where scarcity is not an issue. |
