Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Machine Learning for Healthcare

Machine Learning for Healthcare

Some cases, opportunities, and challenges in applying machine learning to healthcare problems.

Ali Akbar S.

April 27, 2019
Tweet

More Decks by Ali Akbar S.

Other Decks in Technology

Transcript

  1. • What is machine learning (ML)? • Opportunities in machine

    learning for healthcare (ML4HC) • Challenges in ML4HC • Future of ML4HC Outline
  2. Identifying Cats or Dogs Model • Logit model • SVM

    Image Processing • Edge detection • Texture analyser • Color histogram Feature Extraction • Eye position • Eye colour • Nose colour • Fur type • Leg counts
  3. y = σ(β 0 + β 1 x 1 +

    β 2 x 2 + β 3 x 3 ) Logit model from defined features
  4. “...diagnosing and treating diseases believed to be caused by misfolded

    proteins, such as Alzheimer’s, Parkinson’s, Huntington’s and cystic fibrosis.” (Evans et al., 2018)
  5. Bias in ML “...a project to look for skin cancer

    in photographs. It turns out that dermatologists often put rulers in photos of skin cancer, for scale, but that the example photos of healthy skin do not contain rulers. To the system, the rulers (or rather, the pixels that we see as a ruler) were just differences between the example sets, and sometimes more prominent than the small blotches on the skin. So, the system that was built to detect skin cancer was, sometimes, detecting rulers instead.” (Evans, 2019)