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Re-Imagining Core Systems in Legacy Industries | by Brian Gong | Sep, 2024 | Medium

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In the past, automation was limited to repetitive, predictable tasks: think factory assembly lines or simple data entry jobs. But with the advent of large language models (LLMs), the frontier of automation is expanding into more sophisticated, knowledge-intensive domains. Take the case of healthcare — LLMs are now capable of automating the clinical documentation process, one of the most labor-intensive tasks in medicine. For years, doctors and nurses have spent a significant portion of their time on record-keeping, detracting from direct patient care. Estimates suggest that physicians spend nearly two hours on clinical documentation for every hour spent with patients, a costly and inefficient allocation of resources. LLMs like OpenAI’s GPT-4 can now transcribe conversations between patients and providers, summarize key points, and even generate follow-up recommendations. The implications are profound: reducing administrative burdens not only frees up medical staff but also slashes the

Press enter or click to view image in full size Photo by Igor Omilaev on Unsplash Re-Imagining Core Systems in Legacy Industries Brian Gong 8 min read · Sep 30, 2024 -- Listen Share In the past, automation was limited to repetitive, predictable tasks: think factory assembly lines or simple data entry jobs. But with the advent of large language models (LLMs), the frontier of automation is expanding into more sophisticated, knowledge-intensive domains. Take the case of healthcare — LLMs are now capable of automating the clinical documentation process, one of the most labor-intensive tasks in med

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