The global generative AI (GenAI) in healthcare market is expected to reach $14,77-billion by 2030, says Grand View Research, adding that it is anticipated to grow at a CAGR of 36,7% from 2023 to 2030.
Generative models in healthcare are advancing diagnostic accuracy by generating high-resolution medical images. These AI-powered models excel at producing intricate imaging aiding in the detection and diagnosis of critical diseases like cancer, lesions, and abnormalities.
The enhanced image quality enables healthcare professionals to identify subtle anomalies more effectively. Moreover, the efficiency and speed of generative models expedite the diagnostic process enabling prompt intervention and improved patient outcomes.
Generative AI is utilised in drug discovery to create new drug compounds or optimise the existing ones accelerating the drug development timeline. Additionally, it assists in predicting drug properties and potential side effects, offering valuable insights for informed decision-making in the pharmaceutical industry.
Generative AI is a transformative force in healthcare, enabling a profound shift towards personalised medicine. By leveraging an individual’s genetic data and health history, generative AI algorithms can craft tailor-made treatment plans and medications. This innovative approach ensures that medical interventions are precisely aligned with a person’s unique genetic makeup and health circumstances, maximising treatment efficacy and minimising adverse effects.
The potential of generative AI to customise healthcare interventions marks a pivotal advancement in medicine promising a future where treatments are optimised and personalised for everyone, ultimately improving overall healthcare outcomes.
Generative AI’s foothold in the healthcare market of North America has strengthened significantly, showcasing a notable surge in growth. Advances in artificial intelligence and machine learning, particularly generative models, have propelled their applications within healthcare.
From generating medical images for accurate diagnostics to aiding drug discovery processes and personalising treatment plans based on individual genetic profiles, the potential of generative AI is being actively explored and adopted.
Collaborations between research institutions, healthcare organisations, and technology firms, along with substantial venture capital funding and supportive regulatory frameworks, further fuel the integration of generative AI into various healthcare domains. The demand for personalised medicine and a drive towards innovation are key factors contributing to the remarkable growth of generative AI in the healthcare sector throughout North America.
Highlights from the report include:
* Based on function, the medical imaging analysis segment dominated with a revenue share of 28,9% in 2022. Generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), have shown significant promise in generating high-fidelity medical images.
* Based on end-use, the clinical research segment dominated the market with a revenue share of 29,3% in 2022. Generative AI has demonstrated substantial potential in assisting and expediting various aspects of clinical research like drug discovery, optimisation of clinical trial designs, predictive analytics, and optimising research processes.
* The pharmaceutical industry continued to embrace generative AI for drug discovery and development. AI-driven generative models accelerated the process of identifying potential drug candidates and optimising existing ones, reducing the time and cost associated with bringing new medications to market.
* Generative AI is revolutionising healthcare training with realistic virtual simulations. It helps create lifelike patient avatars and interactive surgical scenarios, enhancing the skills of healthcare professionals in a risk-free environment.