{"href":"http://player.captivate.fm/services/oembed?url=http%3A%2F%2Fplayer.captivate.fm%2Fepisode%2F5c7178f6-5ead-4f0c-9fcc-88748a30f589","version":"1.0","provider_name":"Captivate.FM","provider_url":"https://www.captivate.fm","width":600,"height":200,"type":"rich","html":"","title":"Zack Chase Lipton \u2014 The Medical Machine Learning Landscape","description":"How Zack went from being a musician to professor, how medical applications of Machine Learning are developing, and the challenges of counteracting bias in real world applications.\n\nZachary Chase Lipton is an assistant professor of Operations Research and Machine Learning at Carnegie Mellon University.\n\nHis research spans core machine learning methods and their social impact and addresses diverse application areas, including clinical medicine and natural language processing. Current research focuses include robustness under distribution shift, breast cancer screening, the effective and equitable allocation of organs, and the intersection of causal thinking with messy data.\n\nHe is the founder of the Approximately Correct (approximatelycorrect.com) blog and the creator of Dive Into Deep Learning, an interactive open-source book drafted entirely through Jupyter notebooks.\n\nZack\u2019s blog - http://approximatelycorrect.com/\n\nDetecting and Correcting for Label Shift with Black Box Predictors: https://arxiv.org/pdf/1802.03916.pdf\n\nAlgorithmic Fairness from a Non-Ideal Perspective https://www.datascience.columbia.edu/data-good-zachary-lipton-lecture\n\nJonas Peter\u2019s lectures on causality:\nhttps://youtu.be/zvrcyqcN9Wo\n\n0:00 Sneak peek: Is this a problem worth solving?\n0:38 Intro\n1:23 Zack\u2019s journey from being a musician to a professor at CMU\n4:45 Applying machine learning to medical imaging\n10:14 Exploring new frontiers: the most impressive deep learning applications for healthcare\n12:45 Evaluating the models \u2013 Are they ready to be deployed in hospitals for use by doctors?\n19:16 Capturing the signals in evolving representations of healthcare data\n27:00 How does the data we capture affect the predictions we make\n30:40 Distinguishing between associations and correlations in data \u2013 Horror vs romance movies\n34:20 The positive effects of augmenting datasets with counterfactually flipped data\n39:25 Algorithmic fairness in the real world\n41:03 What does it mean to say your model isn\u2019t biased?\n43:40 Real world implications of decisions to counteract model bias\n49:10 The pragmatic approach to counteracting bias in a non-ideal world\n51:24 An underrated aspect of machine learning\n55:11 Why defining the problem is the biggest challenge for machine learning in the real world\n\nVisit our podcasts homepage for transcripts and more episodes!\nwww.wandb.com/podcast\n\nGet our podcast on YouTube, Apple, and Spotify!\nYouTube: https://www.youtube.com/c/WeightsBiases\nSoundcloud: https://bit.ly/2YnGjIq\nApple Podcasts: https://bit.ly/2WdrUvI\nSpotify: https://bit.ly/2SqtadF\n\nWe started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they\u2019re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it!\n\nJoin our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research:\nhttp://tiny.cc/wb-salon\n\nJoin our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning:\nhttp://bit.ly/wandb-forum\n\nOur gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices.\nhttps://app.wandb.ai/gallery","thumbnail_width":300,"thumbnail_height":300,"thumbnail_url":"https://artwork.captivate.fm/3b2be9e1-a367-4678-a0eb-c2bfda9fb3d1/artworks-6tvjy49ttdlhxoxy-et3kka-t3000x3000.jpg"}