Welcome! My research spans statistical machine learning and its applications in healthcare and the sciences. I am an Assistant Professor in the Dept. of Computer Science at Tufts University and a primary faculty member for the Tufts Machine Learning rese
Repository for projects of the course "Machine Learning for Health Care" taught at ETH Zürich in spring 2020 :bookmark_tabs: :robot: :pill: :syringe: :chart_with_upwards_trend: - GitHub - MartinTschechne/ML4H2020: Repository for projects of the course "
NIPS ML4H 2017 : NIPS Workshop on Machine Learning for Healthmchughes
摘要: This volume represents the accepted submissions from the Machine Learning for Health (ML4H) workshop at the conference on Neural Information Processing Systems (NeurIPS) 2018, held on December 8, 2018 in Montreal, Canada.DOI: 10.48550/arXiv.1811.07216 年份: 2018 ...
Mesenchymal Stromal Cells (MSCs) are the preferred candidates for therapeutics as they possess multi-directional differentiation potential, exhibit potent immunomodulatory activity, are anti-inflammatory, and can function like antimicrobials. These capab
- alized gaussian processes for future prediction of alzheimer's disease progression," NIPS Workshop on Machine Learning for Healthcaare (ML4HC), 2017... K Peterson,Ognjen,Rudovic,... 被引量: 7发表: 2017年 Minerva: A Scalable and Highly Efficient Training Platform for Deep Learning Nips W...
Rethinking clinical prediction: why machine learning must consider year of care and feature aggregation. In: Machine Learning for Health (ML4H): Workshop at NeurIPS. 2018. arXiv:1811.07216 [cs.LG]. Davis SE, Greevy RA, Fonnesbeck C, Lasko TA, Walsh CG, Matheny ME. A nonparametric updating...
Introduction to Machine learning with Python, 4h interactive workshop - amueller/ml-workshop-1-of-4
Machine Learning for Health Workshop, ML4H@NeurIPS 2020, Virtual Event, 11 December 2020. Addressing the Real-world Class Imbalance Problem in Dermatology. Wei-Hung WengJonathan DeatonVivek NatarajanGamaleldin F. ElsayedYuan Liu TL-Lite: Temporal Visualization and Learning for Clinical Forecasting. ...
Ag nanoparticles decorated on ZnONR-SNF form “hot-spot” that significantly enhance the surface-enhanced Raman spectroscopy (SERS) signal, resulting in an enhancement factor of 1056 and an experimental detection limit of 1 pg mL−1. Furthermore, a machine learning algorithm is developed ...