Use of AI/Machine Learning Tools to Predict Outcome

Description

In this presentation, Justin Green expresses his gratitude for being appointed as a Fellow for the Hip Society and ORUK, highlighting his excitement about utilizing his background in a new project. He shares how he transitioned from a career in finance and software to medicine, mentioning his ongoing fellowship and PhD in artificial intelligence at Newcastle. Justin discusses his involvement in a project called OpenPredictor, which employs machine learning to identify high-risk patients and improve healthcare pathways.



He emphasizes the importance of supervising machine learning models to avoid spurious outcomes and notes challenges related to data validation and representation within datasets. Justin highlights findings indicating disparities in healthcare access and outcomes among different socioeconomic groups. He reflects on his work with deprivation indices and outcome scores, looking to future research that could provide valuable insights and enhance patient care. In conclusion, he expresses optimism about demonstrating meaningful findings through his fellowship.

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