Active Learning for Phenotyping Tasks
نویسندگان
چکیده
Active learning is a popular research area in machine learning and general domain natural language processing (NLP) communities. However, its applications to the clinical domain have been studied very little and no work has been done on using active learning for phenotyping tasks. In this paper we experiment with a specific kind of active learning known as uncertainty sampling in the context of four phenotyping tasks. We demonstrate that it can lead to drastic reductions in the amount of manual labeling when compared to its passive counterpart.
منابع مشابه
Workshop on NLP for Medicine and Biology associated with RANLP 2013
Active learning is a popular research area in machine learning and general domain natural language processing (NLP) communities. However, its applications to the clinical domain have been studied very little and no work has been done on using active learning for phenotyping tasks. In this paper we experiment with a specific kind of active learning known as uncertainty sampling in the context of...
متن کاملApplying active learning to high-throughput phenotyping algorithms for electronic health records data.
OBJECTIVES Generalizable, high-throughput phenotyping methods based on supervised machine learning (ML) algorithms could significantly accelerate the use of electronic health records data for clinical and translational research. However, they often require large numbers of annotated samples, which are costly and time-consuming to review. We investigated the use of active learning (AL) in ML-bas...
متن کاملApplying Computer-Mediated Active Learning Intervention to Improve L2 Listening Comprehension
: This study aims to apply active learning in a foreign language context to improve L2 learners’ listening comprehension. Participants in this attempt were 56 EFL learners between 13 and 15 years old. To amass the required data, learners went through a ten-week treatment, in which participants in the experimental group received computer-mediated active learning intervention and...
متن کاملComparing Rule-Based and Deep Learning Models for Patient Phenotyping
Objective: We investigate whether deep learning techniques for natural language processing (NLP) can be used efficiently for patient phenotyping. Patient phenotyping is a classification task for determining whether a patient has a medical condition, and is a crucial part of secondary analysis of healthcare data. We assess the performance of deep learning algorithms and compare them with classic...
متن کاملDeep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks
Plant phenomics has received increasing interest in recent years in an attempt to bridge the genotype-to-phenotype knowledge gap. There is a need for expanded high-throughput phenotyping capabilities to keep up with an increasing amount of data from high-dimensional imaging sensors and the desire to measure more complex phenotypic traits (Knecht et al., 2016). In this paper, we introduce an ope...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013