AI Breakthroughs in Patient Care: 7 Leaders Share Their Perspectives

I have used advanced diagnostic technologies in my endodontic practice for many years. In my experience as an endodontist, the use of artificial intelligence (AI) to analyze imaging studies such as cone beam computed tomography (CBCT), which provides three-dimensional images of the internal anatomy of teeth, has dramatically improved both my ability to identify and diagnose abnormalities within roots of teeth that previously would have been difficult or impossible for me to identify with my own eyes.

Each day I see how much of a difference AI makes in helping me understand my CBCT images. AI software identifies anatomical complexities and anomalies that are often difficult or impossible to recognize by a human, and helps guide me to address these anatomical features during endodontic therapy. Recently, I had a case where the AI found a fourth canal in a lower molar that was not apparent from my original examination of the CBCT scan. Identifying this additional canal prior to initiating treatment allowed me to complete a full endodontic treatment and eliminate the need for potential future retreatment of the tooth for the patient.

Although this new technology has greatly enhanced my ability to accurately diagnose and treat endodontic problems, it has not eliminated the role of my clinical judgment. Instead, it provides me with an additional set of highly trained “eyes” to review all of my cases and assist me in planning and executing each procedure. By providing me with this additional resource, I spend significantly less time searching for anatomy during my procedures, because I already know what I will find before I begin. This allows me to provide patients with better outcomes due to early identification of potential problems and comprehensive treatment of those problems. Together with my extensive education and training, and the benefits of using AI analysis of imaging studies, I believe that I can provide my patients with a level of care that was not available when I completed my specialty training.

One way AI has improved patient outcomes in urology is by accelerating and improving the speed and precision of research synthesis and guideline comparisons, thereby supporting better clinical decision-making.

AI tools now enable rapid comparison of EAU, AUA, and other international guidelines, cross-checking them against emerging research and identifying where recommendations align or differ. In daily practice, this is especially valuable for complex or borderline cases, such as prostate cancer risk stratification, non-muscle-invasive bladder cancer follow-up, or treatment selection in LUTS, where slight differences in evidence interpretation can change management. By quickly integrating trial data, guideline updates, and patient-specific factors, AI helps us make more evidence-based and consistent decisions.

This has changed my perspective on technology in healthcare: AI is not about replacing clinicians, but about strengthening clinical reasoning through better access to structured knowledge. It reduces time spent navigating fragmented literature and allows greater focus on thoughtfully applying evidence to the individual patient. Used responsibly, AI becomes a bridge between research and real-world care—ultimately improving outcomes by helping us select the appropriate intervention for the relevant patient in the proper time.

In orthodontics, one of the biggest ways technology has improved patient outcomes is through digital treatment planning and 3D imaging. In our practice we use advanced intraoral scanners to capture highly accurate digital models of the teeth and bite. These scans let us visualize the patient’s anatomy in three dimensions, plan treatments more precisely, and show patients a preview of their expected results before treatment begins.

The software we work with uses powerful algorithms to help predict tooth movement and simulate outcomes for clear aligner therapy and braces. This kind of digital workflow leads to fewer surprises during treatment, more accurate aligner fits, and better overall predictability. In many ways, these tools are the foundation for how AI is being integrated into orthodontics more broadly in the profession, where research shows AI can enhance planning, monitor progress, and support decision-making in real time.

AI tools aren’t just about convenience, they’re essential to delivering personalized, predictable care. Technology gives us better data and clearer communication with patients.

We use AI to identify movement patterns and how people recover sooner in their care. We’re now able to identify patients who are likely to stall or flare at a particular response curve and proactively adjust treatment accordingly. This means fewer chronic cases and more stable recovered patients sooner, moving from reaction to prevention.

My view of technology is that it is a clinical amplifier, not an annoyance. With AI, we can see patterns that we might overlook in a busy clinic. I look into the patient, not at the screen, but data helps create a clearer and more confident decision. But when appropriately used, the care’s humanity remains.

We use AI simulation technology at ProMD Health to show patients what their results will look like before any treatment begins. This has completely eliminated the “expectation vs reality” problem that used to cause disappointment even with technically successful procedures.

Before implementing this tech, about 30% of consultations ended without booking because patients couldn’t visualize outcomes and felt anxious. Now we’re converting closer to 75% because they see themselves with fuller lips or smoother skin right there on the screen. More importantly, patient satisfaction scores jumped dramatically because there are zero surprises–they get exactly what they saw in the simulation.

My perspective shifted from seeing technology as a clinical tool to recognizing it as essential for informed consent. Coming from pancreatic cancer research at Hopkins where outcomes were often uncertain, being able to give aesthetic patients this level of certainty feels revolutionary. They’re making genuinely informed decisions rather than just trusting our descriptions.

The unexpected bonus: our staff spends way less time managing anxious follow-up calls asking “is this normal?” because patients already knew what their healing process would look like. That time now goes to actual patient care rather than reassurance.

I started using Zoom for Healthcare’s AI Companion to handle my session notes, and the difference it’s made is pretty significant. I can now be fully present with my clients instead of splitting my attention between listening and trying to capture everything they’re saying. Before AI note-taking, I would jot notes during the session that would pull me out of the moment. Clients can tell when you’re distracted, even slightly, and it breaks the rapport we’re building. They need to know that I’m completely present, tracking not just their words but their tone, body language, and the pauses between their thoughts.

Now I can give that full attention because I’m confident AI is capturing the most important content. The result is that my sessions go deeper. Clients feel genuinely heard and I’m able to create a more effective, personalized approach. AI handles the documentation so I can do what I’m actually trained to do: be a skilled, attentive guide through their healing process.

I used to see tech as something that could create distance and distraction; more screens, less human connection. But I’ve learned that the right technology actually removes barriers to connection. When AI takes over the administrative burden, it frees us to be more human, not less. That’s made me much more open to exploring how other AI tools might enhance the quality of care I can provide.

One of the most meaningful ways AI has improved patient outcomes in healthcare operations is by reducing breakdowns in communication. For example, missed calls, delayed follow-ups, and scheduling errors that quietly impact care.

At DocVA, we’ve seen AI tools help prioritize and route patient requests more efficiently, flag overdue follow-ups, and support virtual medical assistants with real-time context so patients aren’t falling through the cracks. When patients get faster responses and clearer communication, they’re more likely to show up, adhere to care plans, and feel supported.

What’s changed my perspective is realizing that AI works best when it strengthens human workflows rather than replacing them. In healthcare especially, outcomes improve when trained, HIPAA-compliant staff are empowered by technology, not sidelined by it. The future is all about AI quietly supporting people so care teams can stay focused on patients instead of administrative noise.