​​Step Change Improvement in Molecular Property Prediction with PotentialNet

Paper on a significant improvement in ability to predict molecular properties in drug design. #ML algorithms are getting better and better than classical methods.

Link: https://medium.com/@pandelab/step-change-improvement-in-molecular-property-prediction-with-potentialnet-f431ffa32a2c

#drugsdesign #biolearning #healthcare

​​New paper on #osteoarthritis progression prediction

Link: https://arxiv.org/abs/1904.06236
GitHub (model & code): https://github.com/MIPT-Oulu/OAProgression

#biolearning #healthcare #ML

​​End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

Researchers from #GoogleAi and #Stanford published work today in #Nature that shows great potential to use machine learning to help catch more lung cancer cases earlier and increase survival likelihood.

Link: http://go.nature.com/2LSMaAz

#LungCancer #Cancer #biolearning #healthcare #DL #CV

​​Accelerating MRI reconstruction via active acquisition

Researchers from #Facebook AI propose a new approach to MRI reconstruction that restores a high fidelity image from partially observed measurements in less time and with fewer errors.

Link: https://ai.facebook.com/blog/accelerating-mri-reconstruction/
Paper link: https://research.fb.com/publications/reducing-uncertainty-in-undersampled-mri-reconstruction-with-active-acquisition/

#CV #DL #CVPR2019 #healthcare #MRI #biolearning

​​Unified rational protein engineering with sequence-only deep representation learning

UniRep predicts amino-acid sequences that form stable bonds. In industry, that’s vital for determining the production yields, reaction rates, and shelf life of protein-based products.

Link: https://www.biorxiv.org/content/10.1101/589333v1.full

#biolearning #rnn #Harvard #sequence #protein

​​Understanding Transfer Learning for Medical Imaging

ArXiV: https://arxiv.org/abs/1902.07208

#biolearning #dl #transferlearning

​​Generative Image Translation for Data Augmentation in Colorectal Histopathology Images

#GAN that generates near-real #histology images according to a Turing test with 4 pathologists. The results can be used for training #DL models for detecting rare histological patterns.

ArXiV: https://arxiv.org/abs/1910.05827
Code: https://github.com/BMIRDS/HistoGAN

#CV #healthlearning #biolearning #medical

Using AI to Understand What Causes Diseases

An overview on applying data science in healthcare

Poster: https://info.gnshealthcare.com/hubfs/Publications_2019/ESMO_GI_Final_Poster_Printed_PD_20.pdf
Link: https://hbr.org/2019/11/using-ai-to-understand-what-causes-diseases

#meta #biolearning #dl #medical #healthcare

ProteinNet: a standardized data set for machine learning of protein structure

Link: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2932-0
Github: https://github.com/aqlaboratory/proteinnet

#biolearning #medical #dl

Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach

ArXiV: https://arxiv.org/abs/1912.11027

#Cancer #BreastCancer #DL #CV #biolearning