The Explainable Artificial Intelligence (XAI) system focuses on the effectiveness of AI based on its ability ‘to explain’ decisions. We are extending this ‘ability to explain’ to deliver exceptional healthcare at affordable costs and patient convenience outside of traditional healthcare facilities. XAI framework drives clinical pathways based on machine learning algorithms trained on enormous amounts of data, validated protocols supported by evidence-based learning, and meaningful after-action reasoning. This enables collaboration and a better physician-patient relationship, which contributes to an effective and affordable healthcare system.
Our XAI system includes a tailored kit with wearable or portable medical devices for remote patient monitoring, and a smartphone or tablet app that integrates and seamlessly shares data from these devices to the clinician. The app is embedded with a virtual assistant, enabling AI-assisted voice dialog to enhance the overall user experience. All medical devices chosen are medical grade, noninvasive, senior-friendly, battery powered, and smartphone compatible. The XAI system enables the clinicians and care providers to review the health information in real time and request for an explanation for any generated patient guidelines, thereby validating the model using reinforcement learning techniques.
The XAI system enables continuous remote patient monitoring, leveraging real-time data collection and instant feedback, to deliver enhanced patient satisfaction. The key outcomes include patient-centricity, continuous care, preventive care, and affordable care. This system has delivered increased patient engagement through daily health management. Remote monitoring data determined the need for care intervention based on alarming increase in patient vitals, and data from XAI dialog. It has also enabled care intervention for a group of patients with special needs. For example, remote monitoring of the oximeter data, ordering tests like X-rays, and scheduling appointments promoted independent in-home care for the patients.