AI is making an impact on many industries, contributing to efficiency, advancement and accessibility. The medical and healthcare industry is a perfect example, as AI has played a role in the early diagnosis of various diseases, the development of new drugs and personalized treatments, and has become an ally in the fight against cancer. Of special note this month, AI has proven to be key in the early detection of breast cancer, using its advanced capabilities to identify signs that may go unnoticed during standard exams.
Mammograms have been the standard method for identifying breast cancer in its early stages. However, some small or fast-growing tumors can be difficult to detect, delaying treatment and reducing the chances of success outcome. This disease remains one of the leading causes of death among women worldwide. In Latin America, the Global Cancer Observatory recorded a total of 220.124 breast cancer cases in 2022, with 59.876 related deaths, representing an 8% mortality rate.
AI in the early detection of breast cancer
In response to this reality, there is a need to integrate new technologies that can aid diagnosis and transform healthcare. For example, the AI tool Mia, developed by Kheiron Medical in the UK, successfully identified signs of breast cancer missed by radiologists in 11 women. The key is the use of deep learning algorithms to analyze mammograms and detect minimal abnormalities, improving prognosis through earlier and more accurate diagnoses.
However, for AI tools like Mia to work effectively and without interruption, a new type of critical digital infrastructure with a converged design is needed to support processing of high-performance computing in real time. This is where edge computing comes into play, a technology that brings processing closer to medical devices, reducing the speed of image interpretation and improving diagnostic response times. This is critical to delivering faster, more accurate results and personalized treatment for patients.
Critical digital infrastructure supporting healthcare services
While edge computing is essential to support AI applications in the healthcare industry, it’s also fundamental to have a robust critical digital infrastructure that includes power train solutions and a reliable, efficient cooling chain. The processors driving AI are highly energy-demanding, projected to reach densities of 500 kW per rack or higher for new generations of AI. This means that healthcare centers must employ strategies that enable resources to be available at all times to provide accurate and agile services so patients receive the care they need without delay.
In Latin America, AI's ability to detect early signs of this disease presents a major opportunity to improve healthcare systems, speed up diagnosis times, and reduce patient waiting lists in hospitals. To successfully implement AI-driven solutions in the region, it's necessary to optimize power capacity, leverage solutions that enable the availability and continuity of the AI applications, and workforce training to take full advantage of AI’s benefits.
Today's AI applications demand specialized solutions, and Vertiv is a leader in strategies and solutions to keeping them up and running. Vertiv offers solutions from grid-to-chip, including power management, uninterruptible power supply systems, distribution boards, busway, switchgear, batteries, thermal management - where our liquid cooling solutions are essential to extract the heat generated by GPUs and processors, and a portfolio of services to support the infrastructures from planning and selection, to deployment, maintenance and service. A partnership with Vertiv helps to make AI and high-performance computing (HPC) possible. Learn more about how Vertiv’s solutions can help you adapt to the Future of healthcare here.
