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Cancer treatment

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    Regina Barzilay highlights the imprecision of scientific processes in cancer treatment, emphasizing a probabilistic approach over deterministic models.
    Machine learning can predict cancer types earlier, yet data accessibility remains a critical barrier, taking two years to access significant datasets.
    Breast density laws in the US mandate informing women of cancer risk, but ML models outperform traditional methods based on outdated radiologist observations.
    Despite advances, no drugs developed using machine learning have been approved, indicating a gap in applying ML to drug design.
    Machine learning's role in drug discovery is promising, yet current models lack deep understanding of language structure, limiting NLP applications.

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    4 books and papers cited across these episodes.

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