This interview is part of our new AI in Healthcare series, where we interview the world's top thought leaders on the front lines of the intersections between AI and healthcare.
In this interview, we speak with Neal Liu, Co-Founder and CTO of uCare.ai, to understand how his company is using AI to transform healthcare, and what the future of the healthcare industry holds.
What’s the story behind your company? Why and how did you begin?
NL: Founded in 2016 by myself and Christina Teo, our team of data scientists and technologists came together with one mission: to use data ethically to solve real-world problems and improve lives. By creating the most advanced artificial intelligence capable of making accurate predictions years into the future, our aim is to apply our predictive engine to all aspects of the healthcare industry, to help patients, providers, caregivers, and payers manage patients throughout the lifecycle of their diseases at lower costs. Quoting from Kathy McGroddy, VP of IBM Watson Health, “No one company is big enough to transform an industry on its own. It takes a village to change.” I believe this healthcare ecosystem is still at its infancy and we should see a lot of M&A (merger and acquisition) activities in the coming five to ten years as big players either build or buy technologies/customers.
Please describe your use case and how your company uses AI
NL: Our first use case is to solve the healthcare industry's biggest pain points: risk management, and exploding medical consumption and costs. First and foremost, uCare.io is a technology-enabling company. Our core competency is our proprietary (i) data acquisition model, (ii) infrastructure design and architecture, and (iii) growing knowledge base of insights generated from our AI engine. Using a suite of proprietary deep learning and neural network algorithms built on existing healthcare data, we have used our predictive engine to help prioritize healthcare resources to reduce preventable hospitalization, potentially resulting in significant annual savings in the industry.
We also boast a highly accurate predictive capability by correctly identifying the risk of rehospitalization for a segment of Singaporeans. Technology capabilities & focuses include:
- Agile and business value proposition oriented.
- Focuses on developing algorithms that are well suited for medium-sized data.
- Complex data analytics requires human insight and supervision.
- Narrow, purpose-built A.I.
- Deep learning architectures.
- Scalable and real-time data platform (infrastructure & delivery mode).
Technologies/capabilities that could not be easily cross-replicated include:
- Established context-specific A.I. models (focused on chronic diseases management).
- Ad-hoc analytics and agile A.I. development workflow.
- Access to domain knowledge and experts (especially in local-context, such as collaborations with research institutions, hospitals, and other service providers).
Could you share a specific customer/user that benefits from what you offer? What has your service done for them?
NL: Parkway Pantai, Southeast Asia's largest healthcare provider, has been using our AI to dynamically generate personalized, more accurate hospital bill estimates. Deployed in all 4 Parkway hospitals in Singapore, namely Mount Elizabeth, Mount Elizabeth Novena, Gleneages, and Parkway East, the system has provided a significant 60 percent improvement over the prior bill estimation system in 2 weeks of going live.
The accuracy of the predictions is expected to improve over time as the system collects and references more data through a process of self-learning. Our AI-powered system gives patients more accurate hospital bill estimates and empowers them to make more well-informed decisions on the medical treatment options available. It also allows patients to have greater peace of mind over their healthcare expenditure so they can focus on getting well.
What other AI use cases in Healthcare are you excited about?
NL: We are excited by our suite of products that add value to the healthcare industry. This includes:
– Cost Predictor
– Risk Predictor
– Medical demand forecasts
– Anomaly detection
– Patient-doctor matchmaking
– Health nudges
– Medical Event Flow
– Lead generation
– Dynamic pricing
Where will your company be in 5 years?
NL: Our plan is to continue transforming huge data sets into actionable intelligence that will bring value for businesses. In 5 years, we aspire to transform the landscape of not just healthcare, but additional verticals for the better through continually innovating in our application of machine learning.
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