Eye On AI

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Week Ending 10.06.19

RESEARCH WATCH: 10.06.19

Over the past week, 920 new papers were published in "Computer Science".

Over the past week, 50 new papers were published in "Computer Science - Artificial Intelligence".

Over the past week, 139 new papers were published in "Computer Science - Computer Vision and Pattern Recognition".

  • The paper discussed most in the news over the past week was by a team at Google: "A deep learning system for differential diagnosis of skin diseases" by Yuan Liu et al (Sep 2019), which was referenced 7 times, including in the article How Machine Learning is Transforming Healthcare at Google and Beyond in Towards Data Science. The paper author, Yuan Liu (South China University of Technology), was quoted saying "We believe these limitations can be addressed by including more cases of biopsy-proven skin cancers in the training and validation sets". The paper got social media traction with 244 shares. The investigators developed a deep learning system (DLS) to provide a differential diagnosis of skin conditions for clinical cases (skin photographs and associated medical histories). A Twitter user, @ddonoho, said "Image-based diagnostics... Today: deep learning >= primary care doctors. Tomorrow: deep learning >= specialists. Today #dermatology and #pathology but ⁦ ⁦ how much longer will image categorization be a job for humans?".

  • Leading researcher Yoshua Bengio (Université de Montréal)

Over the past week, 15 new papers were published in "Computer Science - Computers and Society".

Over the past week, ten new papers were published in "Computer Science - Human-Computer Interaction".

This week was very active for "Computer Science - Learning", with 278 new papers.

Over the past week, nine new papers were published in "Computer Science - Multiagent Systems".

  • The paper discussed most in the news over the past week was by a team at New York University: "Finding Generalizable Evidence by Learning to Convince Q&A Models" by Ethan Perez et al (Sep 2019), which was referenced 1 time, including in the article An approach to enhance question answering (QA) models in Tech Xplore. The paper author, Ethan Perez (Rice University), was quoted saying "Our system can find evidence for any answer—not just the answer that the Q&A model thinks is correct, as prior work focused on". The paper got social media traction with 35 shares. A user, @EthanJPerez, tweeted "What evidence do people find convincing? Often, the same evidence that Q&A models find convincing. Check out our #emnlp2019 paper: And blog post: w/ Rob Fergus".

Over the past week, 23 new papers were published in "Computer Science - Neural and Evolutionary Computing".

This week was active for "Computer Science - Robotics", with 59 new papers.


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