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Doctors and healthcare providers are drowning in patient data-EHRs, lab reports, and imaging files-while outdated systems make it harder to manage. Slow, disconnected software creates delays, security risks, and extra work, taking time away from patient care. Finding records, coordinating between departments, and keeping data secure becomes a daily struggle. When systems don't talk to each other, important information gets lost in silos, making collaboration difficult. The result? Delayed treatments, rising costs, and frustrated medical teams. To provide better care, healthcare needs modern, cloud-based solutions that make data accessible, secure, and easy to manage.

Artificial Intelligence in healthcare isn't just a buzzword anymore it's actually changing how hospitals, doctors, and healthtech companies care for people. From summarizing complex medical records to creating detailed radiology reports in seconds, AI is already doing serious work behind the scenes. But there's a hot debate going on: What's the real game-changer Large Language Models (LLMs) or Generative AI? Is one better than the other? Or do they serve different goals when it comes to improving patient outcomes? If you're in healthcare and thinking about how to use AI the right way, this comparison is worth your time.