Discover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
Discover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
AI in the Medical Field: 5 Examples Demonstrating its Efficacy
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AI is revolutionizing healthcare, particularly in clinical workflows, diagnostics and patient management. AI’s strength lies in its ability to streamline processes, reduce workloads and provide fast, accurate results. In the medical imaging field, one of the most significant value propositions for AI has been its capability to flag incidental findings and prioritize worklists. This enables physicians to receive real-time alerts for patients who might otherwise be overlooked, facilitating earlier and more effective interventions. AI’s impact extends across multiple domains of healthcare, as seen in these customer testimonials:
How Does AI Help in the Medical Field?
AI in the medical field optimizes various areas, from diagnostics to patient monitoring, using machine learning models to assist physicians in making informed decisions. For example, AI-powered platforms can sift through thousands of images to flag potential issues, ensuring critical patients are routed to the appropriate physicians. Without AI, many of these patients might remain unknown to the right physicians in the health system.
An additional area in which AI stands out is its ability to streamline communication between departments. The AI-powered systems route the right patients to the right clinicians, helping to avoid delays in care. This not only benefits health systems by improving efficiency, but by improving patient outcomes–even though the patients are often unaware of the technology being used behind the scenes.
AI in the Medical Field: 5 Examples
1. AI in Pulmonary Embolism (PE) Care at Emory Healthcare
Charles Grodzin, MD, Internal Medicine Pulmonologist at Emory Healthcare shared the benefits AI brings to his team’s work in managing PE patients. The system provides real-time alerts, which means physicians no longer need to manually search for patient information. According to Dr. Grodzin, “It alerts my team, both inpatient and outpatient, of PE patients that I don’t have to search for, which is a huge time saver for me, my administrative staff and the PE team.”
Dr. Grodzin recalled a case where AI was instrumental in improving care for a patient in need. “I was out of town, and it was 11 or 12 at night. Through AI, I could access everything I needed remotely and give my team instructions. Without that information, the patient wouldn’t have been treated as effectively.” The AI technology at Emory also streamlines administrative workflows, alerting staff to incoming PE patients, ensuring timely follow-ups and identifying those at risk for chronic thromboembolic disease. This leads to significant cost and time savings and allows clinicians to intervene before complications worsen.
2. AI in Stroke and Vascular Treatment at Lexington Medical Center
Ryan Bell, Imaging Procedural Manager at Lexington Medical Center, emphasized the value of AI in their stroke and vascular treatment workflows. “We were leaving a lot on the table,” Bell explained. Noting how AI helped improve diagnostic turnaround times and enhance care coordination from the emergency department to the interventional suite. He particularly highlighted AI’s ability to cover not only strokes but also vascular conditions like PE and deep vein thrombosis, providing comprehensive coverage.
Bell shared how the introduction of AI significantly reduced the time it took for doctors to be notified of critical results. “I randomly picked three ischemic stroke cases, and from the time those images were sent to when I received a notification on my phone was less than 60 seconds,” he said. AI has enabled teams at Lexington to “call themselves in for strokes,” often arriving at the hospital before emergency calls even went out. This level of efficiency has drastically improved patient outcomes, allowing for faster interventions.
3. AI for Outpatient Imaging at Assuta Hospital
At Assuta hospital in Tel Aviv, AI plays a crucial role in outpatient imaging. Michal Guindy, MD, Head of Imaging and Innovation spoke about the value of AI in flagging potentially urgent conditions in patients who might otherwise appear stable. “In outpatient settings, patients are usually walking in, and no one assumes they are in a dangerous condition. Often, the first person to identify a serious issue is the technician,” she said.
Dr. Guindy shared a story about a patient who came in for a follow-up after brain surgery. The technician assumed the post-op brain bleed was normal, but the AI system flagged it as a concern. This immediate notification allowed Dr. Guindy to intervene, ensuring the patient received the necessary treatment before any complications arose. “AI is going to be the standard of care,” Dr. Guindy stated, “and we need to learn how to live with and enjoy these solutions.”
4. AI for Triage and Surgery at HOAG Hospital
Scott Williams, MD, Medical Director and Chief of Service at HOAG Hospital has seen AI revolutionize the triage process, particularly for aortic dissection (AD) cases. Previously, notifying surgeons of an acute AD involved multiple phone calls and logging into systems, wasting precious time. AI changed that.
Dr. Williams explained, “We recently went live with an acute aortic team alert. AI notifies the appropriate team members, and in one case, the surgeon received the notification while still in the hospital, allowing them to see the patient immediately after the scan.” This accelerated workflow provided a critical window for intervention in what could have been a life-threatening situation. “The bottom line is that the workflow worked,” Dr. Williams said, emphasizing how AI speeds up the process of getting patients the care they need.
5. AI and Staffing Shortages at St. Luke’s Health System
John Borsa, MD, Chair of Radiology at St. Luke’s Health System in Kansas City, has firsthand experience with the impact of AI on addressing staffing shortages. As an interventional radiologist, Dr. Borsa has been deeply involved in the AI adoption process, from the initial decision to implementation and now as an end-user.
“I am looking for solutions to help shore up my faculty shortages,” he explained. “What limited resources I have need to be more efficient, helping us get through more of the day’s work with less mental fatigue.”
One of the AI tools that made a notable difference at St. Luke’s was the incidental PE algorithm. “The incidental PE algorithm has certainly helped our patients, by comparing the time before and after implementation, I can see a clear improvement. Personally, it has improved my comfort level as an interventional radiologist.
Dr. Borsa recounted a specific case that exemplified AI’s impact. While examining a patient for arterial issues in the legs, AI flagged a suspected incidental PE that might have otherwise gone unnoticed. “I was focused on the belly and legs, trying to figure out why the patient had a cold leg. Lo and behold, the AI flagged a suspicious pulmonary embolism. Sure enough, a CT pulmonary angiogram performed earlier confirmed the presence of the embolism.”
This type of “wow” moment is something that Dr. Borsa and his colleagues have experienced with AI. The solution has proven to be a “game changer” in triaging patients, particularly in the context of St. Luke’s radiologist shortage. “It has been critical in helping us manage our workload efficiently.”
The Future of AI in the Medical Field
The integration of AI in the medical field continues to demonstrate its efficacy across multiple healthcare settings. From improving diagnostics and patient care coordination to streamlining communication between departments, AI is playing a transformative role in healthcare. As seen in these examples, Ai medical tools are helping clinicians work more efficiently and effectively, leading to improved patient outcomes.
As AI technology advances, its applications will continue to expand, offering even greater potential for improving healthcare delivery. Whether through triage, outpatient imaging or addressing problems that come along with staffing shortages, AI’s future in medicine is bright, and its impact is already undeniable.
