7 citations · 8 across the 5 of their papers we have counts for
5 papers
An automated approach to extracting positive and negative clinical research results
Xuanyu Shi, Shiyao Xie, Wenjia Wang +2
Failure is common in clinical trials since the successful failures presented in negative results always indicate the ways that should not be taken. In this paper, we proposed an au…
DP-FP: Differentially Private Forward Propagation for Large Models
Jian Du, Haitao Mi
When applied to large-scale learning problems, the conventional wisdom on privacy-preserving deep learning, known as Differential Private Stochastic Gradient Descent (DP-SGD), has…
Distinguishing Transformative from Incremental Clinical Evidence: A Classifier of Clinical Research using Textual features from Abstracts and Citing Sentences
Xuanyu Shi, Jian Du
In clinical research and clinical decision-making, it is important to know if a study changes or only supports the current standards of care for specific disease management. We def…
Extracting and Measuring Uncertain Biomedical Knowledge from Scientific Statements
Xin Guo, Yuming Chen, Jian Du +1
Purpose: This study aims to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements. Design/methodology/approach: Taking card…
Dynamic Differential-Privacy Preserving SGD
Jian Du, Song Li, Xiangyi Chen +2
The vanilla Differentially-Private Stochastic Gradient Descent (DP-SGD), including DP-Adam and other variants, ensures the privacy of training data by uniformly distributing privac…