AI IN MEDICAL DIAGNOSIS: How America’s Major Healthcare Systems Respond to the Disruptive Force of AI by Revolutionizing Diagnostic Imaging, Clinical Decision Support, and Personalized Medicine

AI is revolutionizing medical diagnostics with its potential to spur drastic improvements in hospital processes. AI can process patient images and health records more accurately and quickly than humans can, reducing physician workload, reducing diagnostic errors, and empowering staff clinic to provide more value.

While hospitals that move early are already reaping the value of AI in medical diagnostics, most US hospitals are at the very beginning of the AI ​​transformation curve – and they risk falling behind if they do. don’t move now.

In this report, Business Insider Intelligence examines the value of AI applications in three high-value areas of medical diagnostics – imaging, clinical decision support, and personalized medicine – to illustrate how technology can dramatically improve patient outcomes, reduce costs and increase productivity.

We examine U.S. healthcare systems that have effectively applied AI in these use cases to illustrate where and how providers should implement AI. Finally, we examine how a leading US healthcare system validates AI partners and internally organizes its AI strategy to provide provider organizations with a model of AI innovation.

The companies mentioned in this report are: Aidoc, Allscripts, Amazon, Arterys, Boston Gene, Cabell Huntington Hospital, Cerner, Cleveland Clinic, Epic, Geisinger Health System, Google, HCA Healthcare, IBM, iCAD, IDx, Intermountain Healthcare, Johns Hopkins , Meditech, Microsoft, Mount Sinai, NorthShore University HealthSystem, Oak Street Health, Stanford University, Tempus, UCI Health System, Unanimous AI, Verily, and Yale New Haven Hospital.

Here are some of the key takeaways from the report:

  • The use of AI in diagnostic imaging, clinical decision support and precision medicine offers the greatest opportunities for cost savings and efficiency in any hospital.
  • Most US hospitals have not implemented AI and risk missing out on the technology gain if they do not develop an effective AI strategy.
  • The first healthcare systems in motion are already reaping the rewards of AI in medical diagnostics by improving outcomes, increasing efficiency and reducing costs.
  • The winning strategies used by hospitals undergoing AI transformation reveal how best to seize the opportunity. These strategies highlight the need for an AI strategy underpinned by talent, data aggregation techniques, and partnerships with external vendors.

In its entirety, the report:

  • Describes how AI is disrupting medical diagnosis in US hospitals.
  • Details the top three use cases of AI in medical diagnostics that will create the most value.
  • Identifies transformational strategies that US hospitals can leverage to effectively deploy AI.
  • Predicts how the use of AI will evolve in clinical decision support, diagnostic imaging and precision medicine.

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