In the last decade, the evolution of AI algorithms has significantly enhanced their capability to analyze medical images with remarkable precision. This progress has been particularly noteworthy in the detection and classification of abnormalities within various imaging modalities, including X-rays, CT scans, and MRIs. Despite these advancements, the landscape of AI solutions in the medical imaging market remains fragmented, marked by the existence of over 700 FDA-approved AI solutions. The FDA’s approval process is stringent, focusing on specific findings in particular body parts for distinct types of images such as X-rays, PET scans, or MRIs. The expectation is that this number will see a substantial increase in the coming years.
Introducing an AI solution into a Healthcare Provider’s (HCP) environment poses several challenges. Typically, when an AI solution is deployed, it must seamlessly integrate with the imaging hardware’s software to pre-process images and transmit them back to the hospital system. However, HCPs grapple with multiple hurdles:
- Each hospital may possess a variety of imaging hardware, each equipped with different software systems.
- HCPs need to conduct rigorous evaluation tests on patient data before deploying any AI solution to ensure its efficacy.
- The integration time and associated costs with each AI solution provider are often prohibitive, discouraging the exploration of multiple solutions.
- Hospitals often contend with limited IT bandwidth spread across various departments, making efficient integration a challenge.
Carpl‘s platform strategically addresses these challenges, offering a comprehensive solution for HCPs to evaluate, procure, deploy, and monitor AI solutions in radiology. Through a one-time integration with the hospital’s software system and imaging software (PACS), Carpl eliminates the need for multiple integrations with various AI providers. This not only significantly reduces costs but also streamlines the integration process, saving valuable time for HCPs.
Carpl’s platform functions as an AI co-pilot for radiologists, seamlessly integrating into their existing workflow. By doing so, Carpl increases radiologists’ productivity and also improves medical outcomes. The platform prioritises scans, ensuring critical patients receive timely attention, potentially saving lives.
The increasing number of imaging scans, totalling 3.6 billion X-rays globally with 2 billion in the US alone, has led to a substantial shortage of radiologists. With the growth rate of imaging scans surging over the last decade, the demand for radiologists has also increased. We envision AI playing a pivotal role in bridging this demand gap. The imaging services market in the US, valued at $120 billion with a CAGR of 4.2%, is undergoing transformative shifts. We anticipate that a significant portion of these costs will transition to AI imaging, reflecting the industry’s inclination toward adopting innovative solutions.
At the forefront of Carpl is Vidur, an entrepreneur with a unique blend of medical, technical, and business-building expertise. His decade long experience in medical imaging, first with Mahajan Imaging and then with Carpl, Vidur possesses an unparalleled understanding of the medical imaging industry. His visionary approach has been instrumental in crafting Carpl’s value proposition, effectively addressing the intricacies of AI integration in the field of radiology.
The remarkable progress Carpl has achieved underscores its commitment to navigating the complexities of AI integration in radiology. Some of its customers include marquee names such as University Hospitals Cleveland, Albert Einstein Hospital Sao Paulo and Singapore General Hospital. By enhancing the role of front-line radiologists, Carpl is not only making significant strides in the industry but is also poised to bring AI adoption in medical imaging to the forefront. As partners in this promising journey, we are thrilled to collaborate with Vidur and his team, supporting them in their pursuit of revolutionising medical imaging through AI.