201 citations · 340 across the 6 of their papers we have counts for
7 papers
The Impact of Automatic Pre-annotation in Clinical Note Data Element Extraction - the CLEAN Tool
Tsung-Ting Kuo, Jina Huh, Jihoon Kim +8
Objective. Annotation is expensive but essential for clinical note review and clinical natural language processing (cNLP). However, the extent to which computer-generated pre-annot…
Efficient Determination of Equivalence for Encrypted Data
Jason N. Doctor, Jaideep Vaidya, Xiaoqian Jiang +6
Secure computation of equivalence has fundamental application in many different areas, including healthcare. We study this problem in the context of matching an individual identity…
ModelChain: Decentralized Privacy-Preserving Healthcare Predictive Modeling Framework on Private Blockchain Networks
Tsung-Ting Kuo, Lucila Ohno-Machado
Cross-institutional healthcare predictive modeling can accelerate research and facilitate quality improvement initiatives, and thus is important for national healthcare delivery pr…
Prerequisites for International Exchanges of Health Information: Comparison of Australian, Austrian, Finnish, Swiss, and US Privacy Policies
Hanna Suominen, Henning Müller, Lucila Ohno-Machado +3
Capabilities to exchange health information are critical to accelerate discovery and its diffusion to healthcare practice. However, the same ethical and legal policies that protect…
Natural Language Processing in Biomedicine: A Unified System Architecture Overview
Son Doan, Mike Conway, Tu Minh Phuong +1
In modern electronic medical records (EMR) much of the clinically important data - signs and symptoms, symptom severity, disease status, etc. - are not provided in structured data…
Enhancing Twitter Data Analysis with Simple Semantic Filtering: Example in Tracking Influenza-Like Illnesses
Son Doan, Lucila Ohno-Machado, Nigel Collier
Systems that exploit publicly available user generated content such as Twitter messages have been successful in tracking seasonal influenza. We developed a novel filtering method f…
Predicting accurate probabilities with a ranking loss
Aditya Menon, Xiaoqian Jiang, Shankar Vembu +2
In many real-world applications of machine learning classifiers, it is essential to predict the probability of an example belonging to a particular class. This paper proposes a sim…