EHNOTE

  In ophthalmology, time is one of your most valuable resources—second only to clinical precision. And let’s be honest, precision often depends on having enough time in the first place. So, it won’t be wrong to say, time is the most valuable resources. Whether you’re performing a cataract evaluation, planning a  refractive surgery , or managing a chronic dry eye patient, the speed and accuracy of your documentation directly influence both patient experience and clinical outcomes. Yet, for many ophthalmologists, traditional  EHR systems  remain a constant source of frustration. Endless clicking. Repetitive data entry. Navigating through screens that look the same for every visit, regardless of the case. And somewhere in the back of your mind—the worry of missing a crucial detail in the chart. But what if your EHR could work the way you do? What if it could adapt to your specialty, subspecialty, and even the unique flow of your practice? That’s exactly where self-confi...

  Software as a Medical Device (SaMD)  refers to standalone software that performs medical functions (for diagnosis, treatment, monitoring, etc.) without being part of a hardware device. In recent years, such software – especially AI-driven tools – has become widespread in health care. Recognizing the unique risks and innovation potential of SaMD, the FDA (via its Digital Health Center of Excellence) has embarked on a series of new policies and guidance's. In short, the FDA aims to regulate SaMD with a  risk-based, life-cycle approach  that protects patients while enabling innovation. How FDA Regulates SaMD Today The FDA treats SaMD under its existing medical device laws, using established pathways (510(k), De Novo, or PMA) based on risk. Simply put, if a software function meets the definition of a medical device, it is evaluated like any other device. The FDA focuses oversight on higher-risk software (e.g. diagnostic algorithms) and often exercises  enforcement...

  When DeepMind’s AI hit a 94.5% accuracy rate diagnosing retinal conditions—matching top  ophthalmologists —it wasn’t just a tech flex. It was a glimpse into what’s possible when AI steps into your world, not as a rival, but as a trusted colleague. Picture this: an assistant who gets your workflow, picks up on your clinical quirks, and respects your time constraints. That’s what  AI in ophthalmology  is starting to look like. Your Wingman, Not Your Replacement Let’s get one thing straight— AI  isn’t here to take your place. Instead, think of it as a partner that amplifies what you already do so well. Those deep learning models crunching OCT scans, fundus photos, and slit-lamp images? They’re spotting diabetic retinopathy, AMD, glaucoma, and corneal issues with precision that rivals expert panels. But here’s the kicker: they’re designed to support you, not steal the show. Take this example—a virtual assistant powered by machine learning classified eye disorders ...