A psychiatrist with an engineering background embarked on a journey to learn natural language processing (NLP) and develop a clinical signal extraction tool for C-SSRS/PHQ-9 assessments within 48 hours. Despite initial struggles with understanding machine learning concepts and tools, the physician successfully created a working prototype using rule-based methods and OpenAI API integration. The project highlighted the challenges of applying AI in healthcare, particularly due to the subjective and context-dependent nature of clinical tools like PHQ-9 and C-SSRS. This experience underscores the need for a bridge between clinical expertise and technical development to enhance healthcare AI applications. Understanding and addressing these challenges is crucial for advancing AI's role in healthcare.
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