The health industry is seeing increased patient disengagement, driving organizations to adopt non-traditional care settings and technology. A blog discusses top healthcare use cases, including improved patient experience through AI chatbots, predictive analytics to avoid unnecessary medication or surgery, dementia detection using an iPhone, and early heart disease detection using AI algorithms and wearable devices. The blog highlights the transformative impact of AI applications in healthcare for improved patient outcomes in 2023.
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Introduction
Within the transforming health industry, patient disengagement is emerging as a pressing trend, as organizations are working hard to win back the trust of patients and adapt to non-traditional care settings and better consumer-centric approaches. Since COVID-19, the adoption of technology and digitization has radically changed the healthcare environment, enabling patients with more individualized healthcare delivery options.
Use Case 1: Devising a Better Patient Experience
Automation and various AI applications in healthcare play a vital role in enhancing the patient experience. For example, a virtual assistant chatbot can help patients receive expert medical advice without having to travel. Saal has developed a virtual chat assistant for the Department of Health (DoH) Abu Dhabi, as an example of such innovation.
Use Case 2: Avoid Unnecessary Medication or Surgery
Predictive analytics can identify patients at risk of diseases that may necessitate specific surgeries or medication. ConsumerMedical has implemented predictive analytics to identify such patients and explore medication possibilities instead of surgeries.
Use Case 3: Dementia Detection Using iPhone
Cognetivity Neurosciences has developed a 5-minute cognitive assessment test on an iOS device like an iPhone to detect early signs of dementia, using various algorithms to cluster the performance based on accuracy, response time, and other factors.
Use Case 4: Early Heart Disease Detection
Eko AI has developed a smart algorithm capable of accurately identifying sounds associated with aortic stenosis (AS) with a 97% accuracy rate, aiding in the early detection of heart diseases. Many wearable devices are available in the market that can track heart rates in real-time, further aiding in the identification of anomalies.
Final Thoughts
AI applications in healthcare have significantly enhanced patient care and outcomes. As innovation and technology continue to evolve rapidly, the involvement of AI is expected to grow, catering to improved and informed patient outcomes. For evolving companies, AI can redefine work processes, automate customer engagement, and offer practical solutions for sales processes and customer engagement.
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