Medicine is a complex, costly and high-impact field, facing challenges in data management, diagnostics and cost reduction. AI offers solutions to these issues, enhancing care and cutting costs. However, its adoption lags behind other industries, underscoring the need to address key barriers. In a comprehensive review, published in the journal Healthcare, researchers from the College of Engineering and Computer Science at Florida Atlantic University in collaboration with Marcus Neuroscience Institute, Boca Raton Regional Hospital – part of Baptist Health – identified the current shortcomings of AI in health care and explored its possibilities, realities and frontiers to provide a roadmap for future advancements.

Artificial intelligence is revolutionizing modern medicine by optimizing administrative workflows, enhancing diagnostic accuracy, and potentially improving patient outcomes. With health care systems worldwide struggling with rising costs, staff shortages and the increasing demand for personalized care, AI presents a transformative opportunity,” said Frank D. Vrionis, M.D., senior author and Chief of Neurosurgery at Marcus Neuroscience Institute – part of Baptist Health – at Boca Raton Regional Hospital. While AI offers promising solutions, its adoption remains hindered by issues such as data privacy concerns, regulatory hurdles and the complexity of AI models.

According to the researchers, the health care industry faces numerous challenges, including administrative inefficiencies, diagnostic errors, high costs and a shortage of skilled professionals. Administrative inefficiencies in scheduling, billing and record management often lead to errors and delays. Integrating AI into legacy systems is difficult due to interoperability issues and data privacy regulations like HIPAA.

The future of AI in health care is incredibly promising, but realizing its full potential requires overcoming several challenges, said Stella Batalama, Ph.D., dean, FAU College of Engineering and Computer Science. AI can streamline routine tasks, minimizing human error and allowing medical professionals to dedicate more time to patient care. Predictive analytics can enhance resource allocation and patient management, while AI-powered models aid in early disease detection and personalized treatments. Additionally, AI-driven robotic systems can increase precision in minimally invasive procedures and enable remote surgeries. Looking ahead, real-time AI-assisted rehabilitation could revolutionize patient recovery, improving outcomes on a global scale.

Source: https://www.fau.edu/newsdesk/articles/ai-medicine-headways-hurdles