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How to Build a Medical AI App Like GalenAI: Key Features, Process & Development Cost

The global healthcare sector is on the cusp of a revolution through the power of artificial intelligence (AI) enhancements. Artificial intelligence is changing the way we move through healthcare systems and how providers give care, from predictive diagnosis to personalized treatment. AI-powered apps are leading the way to change the health market; one of the examples is GalenAI, which integrates medical AI to assist doctors with clinical decision-making. AI in healthcare is a fast-growing market for better, smarter and more intelligent healthcare and creating medical AI apps like GalenAI is not simply a dream, it is a prudent business initiative.

The Rise of Medical AI: Industry Insights & Statistics

AI in healthcare is poised to reach $187 billion by 2030, taking an estimated CAGR rate of 37% between 2023 and 2030 (Statista). Medical AI apps are solving major bottlenecks: radiology, diagnostics, patient engagement, and workflow automation. With over 50% of healthcare organizations having adopted AI-based solutions, it is clear that the future of medicine is digital.

Who Leads the Space? Spotlight on GalenAI

Of the many players, GalenAI has emerged as a leading industry presence. Described as a "clinical co-pilot," GalenAI combines natural language process (NLP), machine learning, and physician, to assist with documentation, coding, and even initial diagnosis. A model for anyone looking to build a clinical AI, its unprecedented integration with EHRs and HIPAA compliant architecture sets the benchmark.

For a deeper dive into this topic, check out the full article here: Building GalenAI: Key Features & Costs

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