Understanding Hidden Bias in Healthcare Machine Learning

Healthcare ML models often learn patterns influenced by clinical decisions.

Key sources of bias include:

• Test ordering behavior
• Admission decisions
• Treatment prioritization
• Resource constraints

Understanding these factors is essential for building reliable models.

My work focuses on applying machine learning with awareness of these dynamics.

I am open to remote roles globally.

Follow my work here:

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