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How HELF AI uses the technology to tackle the severe shortage of healthcare manpower

How can Artificial Intelligence (AI) promote greater access to information in healthcare? For Dr Reid Lim, a medical doctor and founder of the Health Expert Language Framework (HELF), the answer lies in using the technology to provide quick, accurate responses and insights into a wide range of medical queries and clinical scenarios.

HELF AI helps users—seasoned physicians, medical students, or healthcare professionals—with condition classification, evidence review, and much more.

“HELF AI offers numerous advantages, positioning itself as a medical superintelligence that seamlessly integrates as an AI backend. Its benefits include immediate access to medical insights, support for healthcare professionals by reducing their workload, enhanced accuracy in clinical decisions, guidance on complex ethical dilemmas, and decision support. Additionally, HELF extends its utility to public-facing roles in education and preventive health,” explains Dr Lim in an email interview with e27.

One month after its beta release, HELF has begun fostering partnerships with potential collaborators. It is launching pilot programmes that include integrating HELF into an Electronic Medical Records (EMR) system in a vast country with many unserved areas still relying heavily on paper records.

According to Dr Lim, it also has another pilot that involves the platform acting as the AI backend for a client-facing startup dedicated to promoting good sleep and healthy habits.

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HELF is now available on both Google Play and the App Stores, and it will continue to be available for free for the general users. This is part of the platform’s commitment to democratising accurate healthcare information worldwide.

In this conversation, Dr Lim explains the problems that the platform aims to solve and his upcoming plans for it.

The following is an edited excerpt of the conversation.

Can you tell us more about what inspired you to build this solution? What was the development process like?

My drive to develop HELF is fueled by my keen awareness of the profound disparities in global healthcare. As a medical doctor, I personally witnessed these challenges. One of the most critical challenges, intensified by the COVID-19 pandemic and subsequent human burnout, is the severe shortage of healthcare manpower.

This issue is particularly acute in rural and underserved areas, where there simply aren’t enough medical professionals to meet the population’s needs. This shortage results in inadequate care and excessively long waits for medical attention, worsening health outcomes.

Additionally, the rising healthcare costs are becoming a crisis affecting both developed and developing nations. In countries such as the US, medical expenses are a leading cause of bankruptcy, placing enormous financial burdens on individuals and families. Even with insurance, the high costs of treatments and medications can lead to significant debt or deter people from seeking necessary care.

In Singapore, rising healthcare costs for our ageing population are a constant point of consternation. On the flip side, in many parts of the developing world, healthcare infrastructure is deficient or entirely non-existent, leaving populations vulnerable.

HELF acts as a medical superintelligence that transcends traditional boundaries within the healthcare landscape. HELF enhances these platforms’ capabilities by seamlessly integrating itself as the AI backend for solutions such as Electronic Medical Records and Hospital Informatics Systems.

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Additionally, it can adapt to various roles, serving as an AI assistant to doctors, nurses, and other healthcare professionals or offering expert insights for preventive health measures. It can also be used as a wellness assistant for the lay public, guiding the everyday person to better health.

Thus, HELF can significantly extend the reach of the existing medical workforce, compensating for manpower shortages. It acts as a force multiplier, taking on routine tasks to allow human healthcare professionals time and breath to concentrate on direct patient care.

Ultimately, HELF’s capacity to democratise access to quality healthcare information and expert guidance has the potential to make healthcare more equitable worldwide. It represents a significant step toward a future where quality medical care is a basic right accessible to everyone, regardless of geographic or economic barriers. For developed nations, HELF can help augment manpower, enhance efficiency, and reduce the overall cost burden.

The development process involves creating a compound AI framework comprising multiple components that work together to offer accurate insights based on any health-related queries. HELF can powerfully parse unstructured data to arrive at guidance for any clinical scenario.

Who are your users, and how do you acquire them?

HELF operates on both B2C and B2B fronts. Our primary B2C users include the general public who seek to educate themselves about health matters. They can easily access HELF through our website or by downloading our apps, where they can directly pose questions and receive answers. Basic usage will remain forever free.

On the B2B side, HELF is a SaaS platform offering plug-and-play APIs that can be seamlessly integrated into any project, whether it’s a new venture or established systems such as EMR or preventive health platforms. Therefore, our user base extends to healthcare students, professionals, and institutions eager to incorporate AI into their workflows.

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We acquire users through a strategic mix of partnerships, academic collaborations, and direct outreach to healthcare organisations. The proven accuracy and reliability of our platform enhance its credibility, fostering organic growth through user referrals and positive testimonials.

What is your business model? What is your strategy to become a sustainable business?

Our business model operates on two fronts: B2C and B2B. On the B2C side, we offer a subscription service where users can access different tiers of features based on their specific needs and usage thresholds. For the B2B segment, we generate revenue through API usage and also benefit from strategic partnerships based on a cost-sharing model.

To ensure sustainability and growth, we are committed to continuously innovating and expanding our AI’s capabilities to reach a broader market and scale our user base globally. Economies of scale will become increasingly advantageous as we expand. Furthermore, we seek partnerships with healthcare providers and insurers to integrate HELF more deeply into the healthcare ecosystem.

Have you raised any funding?

We have not yet raised funding, but we are actively looking to collaborate with strategic investors who share our vision of building a medical superintelligence that will serve as a cornerstone for the healthcare industry.

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This funding and partnership will bolster our research and development efforts and accelerate HELF’s deployment across broader markets.

What is your focus for 2024?

In 2024, our dual focus is on technological enhancement and expanding practical applications with partners.

Technologically, we are developing robust pipelines for continuous medical learning, ensuring that HELF remains abreast of the latest healthcare guidelines and events. This constant updating is crucial for maintaining the relevancy and effectiveness of our AI solutions.

On the business front, we aim to deepen market penetration and establish sustainable revenue streams through collaborative use cases with our partners. These initiatives are aimed at demonstrating the practical benefits of HELF in diverse healthcare settings and driving broader adoption of our technologies.

Image Credit: HELF

The post How HELF AI uses the technology to tackle the severe shortage of healthcare manpower appeared first on e27.

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