The Dawning of AI in Healthcare
The landscape of healthcare is witnessing a remarkable transformation, driven by the relentless advancement of artificial intelligence (AI). This revolution is not just reshaping clinical practices but is also enhancing the precision of diagnostics and expanding the boundaries of medical knowledge. Central to this evolution is the work of investors like Yazan al Homsi, who have recognized the potential of AI to alter the fabric of healthcare fundamentally. Al Homsi’s insights into the capabilities of AI platforms, particularly Treatment AI (CSE: TRUE, OTC: TREIF, Frankfurt: 939) , highlight a future where technology and medicine converge to create unprecedented efficiencies and accuracies.
Yazan al Homsi on the Pioneering AI Library in Healthcare
“What they have is, or what they’ve established in six, seven years is, they built the world’s largest library for LLMs for basically collecting all the case studies on diseases,” explains Yazan al Homsi, a leading figure in the integration of AI within healthcare. His involvement with Treatment AI showcases a commitment to leveraging AI for comprehensive medical solutions. This extensive library has become a cornerstone for Treatment AI, encapsulating vast arrays of data on common diseases, and enhancing the diagnostic processes.
“So right now they have most of the common diseases in their library,” Al Homsi continues. This repository is not just a static collection of data but a dynamic resource that grows continuously as new case studies and medical findings are added. The depth and breadth of this library allow for an AI-driven approach that surpasses traditional methods in both speed and accuracy.
Al Homsi is particularly critical of conventional online medical advice, often leading to misinformation. “It means that they essentially have a front-end platform that you as a user or myself can, instead of going today, there is a billion person every day, they go to Dr. Google and say, ‘I’ve got XYZ,’ and Dr. Google spews garbage.” In contrast, Treatment AI offers a refined, data-backed alternative that significantly reduces the chances of error. “What Treatment AI has different is the accuracy is way higher. It’s 92% accurate because they spent so many years building that library based on case studies, based on so much data that they…” he notes, emphasizing the meticulous effort involved in creating such a resource.
Impacts and Innovations: Education and Diagnostic Solutions
Integrating AI into medical education represents a significant leap forward, driven by platforms like Treatment AI. Yazan al Homsi highlights the dual benefits of this technology, particularly its impact on the educational framework within medical and nursing schools. “The business model is to focus on two sides. So the first side is to focus on the education side, so medical and nursing schools,” al Homsi points out. Within these institutions, AI’s role is multifaceted, extending from curriculum development to the administration of examinations.
“In medical schools, their AI has been able to put medical tests for doctors and also rate them, and with a very high accuracy,” says al Homsi. This capability not only streamlines the creation of exams but also ensures their relevance and rigor. It significantly reduces the administrative burden, allowing educators more time to focus on teaching rather than on logistics. “What medical schools like about that is the process of putting an exam is tedious and takes time. So they would go on a recurring revenue model with them, they pay them, I don’t know, $25,000 per year,” he explains.
Furthermore, this technological adoption in educational settings serves a dual purpose by indirectly promoting Treatment AI’s platform. “But the other benefit is these medical schools become a de facto selling company for treatment, because what they’ll do is, now their doctors or their medical doctors that are learning are saying, ‘Okay, well, this is very interesting. Maybe I can download the app myself and pay the monthly fee and get myself accustomed ahead of the exam,'” al Homsi elaborates. This strategy not only enhances learning but also familiarizes future healthcare providers with advanced AI tools, ensuring a tech-savvy workforce.
The diagnostic capabilities of Treatment AI are equally revolutionary. Al Homsi describes a scenario that illustrates the user-friendly and intuitive nature of the platform: “So let’s say you have a lower back pain and you’re saying, ‘Okay, I’ve got a lower back pain. I don’t know what it is.’ It asks you, ‘Where are you feeling it?’ And then you can see on the app, it can help you point to where in your body, which side of your lower back, and so on. So within 20 questions, you can get to the why or what it is that most likely you have.” This interactive and precise method of diagnosis not only aids in quicker understanding but also in more accurate treatment planning.
The Business Model and Market Integration
The strategic approach of Treatment AI in the healthcare market is innovative, focusing on long-term integration and partnership with both educational institutions and healthcare providers. Yazan al Homsi elucidates, “The business model focuses on two sides. So the first side is to focus on education, medical, and nursing schools.” This model not only ensures a steady stream of revenue through subscriptions but also embeds the technology into the fabric of future medical practices.
On the healthcare provider front, Treatment AI is making significant inroads. “The other side of the business, which is the longer side of sales, and they currently have two companies in negotiations or in pilot stage, it’s on the healthcare provider side,” al Homsi reveals. This aspect of the business model demonstrates the platform’s adaptability and potential for widespread adoption in clinical settings.
One of the key markets for Treatment AI is Vancouver, Canada, where the platform has been actively involved in pilot projects and investment discussions. The choice of Vancouver is strategic, leveraging Canada’s supportive environment for technological innovation and its robust healthcare system. The integration of AI tools in such a setting not only improves patient care but also positions Treatment AI as a pivotal player in the North American healthcare sector.
Looking Ahead: The Future of AI in Healthcare
As we look to the future, the trajectory of AI in healthcare is set to alter how medical care is delivered and managed dramatically. According to Yazan al Homsi, the next decade will see an even greater integration of AI systems into everyday healthcare processes. The World Economic Forum predicts that AI will enhance connectivity, improve predictive care, and boost both patient and staff experiences.
“AI in healthcare will help detect patterns and connect systems. This will allow for a network of seamless sharing of data, to anywhere, from anywhere. This shared data and information will create life-saving connectivity across the globe,” al Homsi comments, envisioning a future where AI not only supports but also drives clinical decision-making and patient management.
With pioneers like Yazan al Homsi at the helm, the path forward for AI in healthcare is promising and revolutionary. Treatment AI, with its comprehensive library and sophisticated diagnostic tools, stands as a testament to the potential of artificial intelligence to reshape an entire industry.
