77 citations
- Harvard UniversityUS11 papers
- Brigham and Women's HospitalUS9 papers
- Harvard University PressUS7 papers
- Maastricht UniversityNL7 papers
- Dana-Farber Brigham Cancer CenterUS5 papers
- Charité - Universitätsmedizin BerlinDE4 papers
- Dana-Farber Cancer InstituteUS4 papers
- Humboldt-Universität zu BerlinDE4 papers
- Massachusetts Institute of TechnologyUS4 papers
- Technical University of MunichDE4 papers
- Boston Children's HospitalUS3 papers
- Cornell UniversityUS3 papers
Showing 2019 · cs.LGShow all
2 papers · 2 filters
cs.LG2019★ 1 cited
Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports
Neil Deshmukh, Selin Gumustop, Romane Gauriau +6
Although machine learning has become a powerful tool to augment doctors in clinical analysis, the immense amount of labeled data that is necessary to train supervised learning appr…
cs.LG2019★ 4 cited
Augmenting Gastrointestinal Health: A Deep Learning Approach to Human Stool Recognition and Characterization in Macroscopic Images
David Hachuel, Akshay Jha, Deborah Estrin +3
Purpose - Functional bowel diseases, including irritable bowel syndrome, chronic constipation, and chronic diarrhea, are some of the most common diseases seen in clinical practice.…