Breaking Down AI: 10 Real Applications in Healthcare

Rapid advances in digital technology are redefining the way businesses operate and deliver value. Digital technologies—including artificial intelligence (AI), machine learning, and augmented reality, among others— are transforming every industry. They’re accelerating innovation, improving decision making, automating and speeding up processes, and saving overall costs.

The healthcare industry is no exception. It’s being profoundly influenced by this ongoing digital revolution. Health leaders today recognize that innovation requires moving beyond the use of electronic medical records (EMRs) and embracing key principles of digital transformation.

The care that patients receive—and the methods in which hospitals deliver care— has been dramatically transformed. With the introduction of advanced technologies and the increasing availability of data. Systems of record like EMRs have laid the foundation for intelligent healthcare. Applying advanced analytics to massive amounts of data from internal and external sources like clinical analytics and environmental systems can help health organizations glean deeper insights.

These systems of insight are the next evolution of digital transformation. With better access to the right data at the right time. Health leaders can reduce operating costs, improve quality of care, increase the involvement of consumers in the care process, and optimise provider satisfaction.

Explore how AI and advanced analytics offer new strategies for healthcare through the convergence of your available physical, digital and biological data. Find out how these capabilities help enable predictive care, such as identifying early warning signs of disease in high-risk patients and recommending more precise treatment based on similar patient data.

In this E-book “Breaking Down AI: 10 Real Applications in Healthcare” you will discover:

practical use cases for applying AI and data analytics to make healthcare more efficient while improving clinical quality and health-related outcomes. Access and interact with a variety of scenarios, including:

• Sharing and analysing clinical data to deliver targeted health services and improve outcomes through predictive care.
• Using operational data to optimise your management of claims, staffing and overall costs.
• Detecting and preventing fraudulent claims and other abuses based on behavioural patterns.

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