Resource of free step by step video how to guides to get you started with machine learning.
Thursday, June 24, 2021
Building AI models for healthcare (ML Tech Talks)
In this session of Machine Learning Tech Talks, Product Manager Lily Peng will discuss the three common myths in building AI models for healthcare. Chapters: 0:00 - Introduction 1:48 - Myth #1: More data is all you need for a better model 6:58 - Myth #2: An accurate model is all you need for a useful product 9:15 - Myth #3: A good product is sufficient for clinical impact 12:19 - Conversation with Kira Whitehouse, Software Engineer 34:48 - Conversation with Scott McKinney, Software Engineer Resources: Deep Learning for Detection of Diabetic Eye Disease: Gulshan et al, Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA 2016 → https://goo.gle/3gVhTxs A major milestone for the treatment of eye disease De Fauw et al, Clinically applicable deep learning for diagnosis and referral in retinal disease. Nature Medicine September 2018 → https://goo.gle/35Sfs9C Assessing Cardiovascular Risk Factors with Computer Vision. Poplin et al, Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nature Biomedical Engineering. March 2018 → https://goo.gle/3qkg01I Improving the Effectiveness of Diabetic Retinopathy Models: Krause et al, Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy. Ophthalmology August 2018 → https://goo.gle/3gR8d8n Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program. Raumviboonsuk et al. NPJ Digital Medicine. April 2019 → https://goo.gle/2SmyXUO Healthcare AI systems that put people at the center: Beede et al, A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy. CHI '20 April 2020 → https://goo.gle/3ja6TyP Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study. MScPH, Yuchen Xie, Quang D. Nguyen BEng, Haslina Hamzah BSc, Gilbert Lim, Valentina Bellemo MSc, Dinesh V. Gunasekeran MBBS, Michelle Y. Yip, et al. The Lancet → https://goo.gle/3zVec3q Catch more ML Tech Talks → http://goo.gle/ml-tech-talks Subscribe to TensorFlow → https://goo.gle/TensorFlow
Subscribe to:
Post Comments (Atom)
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
JavaやC++で作成された具体的なルールに従って動く従来のプログラムと違い、機械学習はデータからルール自体を推測するシステムです。機械学習は具体的にどのようなコードで構成されているでしょうか? 機械学習ゼロからヒーローへの第一部ではそのような疑問に応えるため、ガイドのチャー...
-
#deeplearning #noether #symmetries This video includes an interview with first author Ferran Alet! Encoding inductive biases has been a lo...
-
How to Do PS2 Filter (Tiktok PS2 Filter Tutorial), AI tiktok filter Create your own PS2 Filter photos with this simple guide! 🎮📸 Please...
-
#ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane requirements...
-
K Nearest Neighbors Application - Practical Machine Learning Tutorial with Python p.14 [Collection] In the last part we introduced Class...
-
Challenge scenario You were recently hired as a Machine Learning Engineer at a startup movie review website. Your manager has tasked you wit...
-
We Talked To Sophia — The AI Robot That Once Said It Would 'Destroy Humans' [Collection] This AI robot once said it wanted to de...
-
Programming R Squared - Practical Machine Learning Tutorial with Python p.11 [Collection] Now that we know what we're looking for, l...
-
RNN Example in Tensorflow - Deep Learning with Neural Networks 11 [Collection] In this deep learning with TensorFlow tutorial, we cover ...
No comments:
Post a Comment