The Visionaries – Generative AI in MedTech

At HecoAnalytics we advise on the application of Artificial Intelligence (AI) to MedTech as well as deploying AI to deliver health economic solutions for our clients. AI in MedTech encompasses the integration of advanced computational technologies into medical and healthcare practices. AI encompasses a range of techniques, notably machine learning, natural language processing and computer vision, which enable systems to interpret complex medical data. These technologies are revolutionising MedTech by improving diagnostic accuracy, personalising patient care, and optimising treatment plans. For example, AI algorithms can analyse medical images, such as X-rays and MRIs, with exceptional speed and precision, assisting radiologists in detecting anomalies that might be missed by the human eye.

Whilst AI has been in the public consciousness for some time, renewed interest has surged in generative AI, particularly with publicly accessible platforms such as ChatGPT and Google’s Bard, which excel in producing human-like text. Unlike traditional AI systems that are designed for analysis or prediction, generative AI models focus on creation, employing advanced algorithms like neural networks to understand and replicate complex patterns and styles inherent in the data they are trained on. In medical imaging, generative AI models like Generative Adversarial Networks (GANs) are used to enhance image quality, generate synthetic medical images for training purposes and create detailed 3D models from 2D scans, aiding in accurate diagnosis and treatment planning. Furthermore, generative AI has significant potential in personalised medicine, tailoring treatments and drug dosages to individual patient profiles by analysing vast datasets of medical records and genetic information.

there is general awareness of the existence of AI and its application to healthcare, another growing trend in healthcare over the last decade of significance is the move to value-based care. There is never enough money to satisfy society’s healthcare needs, and this problem is growing rapidly. In summary, in the foreseeable future it will not be possible to commission health tech products without clear evidence of the health economic benefit that the new product affords. Interestingly, such analyses of health economics such as cost-effectiveness have commonality with the mathematical approaches of AI. At HecoAnalytics we are harnessing cutting-edge AI to allow evaluation of new MedTech technologies to make this an efficient process, giving access to these resources rather than traditional labour-intensive paper-based reports. AI’s ability to process and analyse vast amounts of data can help identify the most efficient allocation of resources, predict patient outcomes, and evaluate the cost-benefit of various healthcare strategies. It can also assist in modelling the long-term economic impacts of healthcare decisions, considering disease progression, quality of life and potential healthcare savings. This will lead to more informed, data-driven decisions that balance patient needs with economic sustainability.

Read more in our brand-new publication, The Visionaries