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Found 13 papers, 4 papers with code
Intelligent Analyses on Storytelling for Impact Measurement
The focus lays on two tasks: determining which sentiment a fragment contains (sentiment analysis) and investigating which fundamental social rights (education, employment, legal aid, etc.)
An exploratory data analysis: the performance differences of a medical code prediction system on different demographic groups
This study aims to investigate further imbalance in a medical code prediction dataset in terms of demographic variables and analyse performance differences in demographic groups.
Synthetic Data Generation and Multi-Task Learning for Extracting Temporal Information from Health-Related Narrative Text
Also, we propose a novel multi-task temporal information extraction model and investigate whether multi-task learning can contribute to performance improvement by exploiting additional training signals with the existing training data.
Building blocks of a task-oriented dialogue system in the healthcare domain
There has been significant progress in dialogue systems research.
DS-MS-TCN: Otago Exercises Recognition with a Dual-Scale Multi-Stage Temporal Convolutional Network
A cohort of 36 older adults participated in laboratory settings, supplemented by an additional 7 older adults recruited for at-home assessments.
Eating Speed Measurement Using Wrist-Worn IMU Sensors in Free-Living Environments
Experimental results shows that the proposed approach achieves a mean absolute percentage error (MAPE) of 0. 110 and 0. 146 in the FD-I and FD-II datasets, respectively, showcasing the feasibility of automated eating speed measurement.
A Multi-Stage Temporal Convolutional Network for Volleyball Jumps Classification Using a Waist-Mounted IMU
In this study, an unobtrusive system with a single inertial measurement unit (IMU) on the waist was proposed to recognize the types of volleyball jumps.
Otago Exercises Monitoring for Older Adults by a Single IMU and Hierarchical Machine Learning Models
The results showed the potential of monitoring the compliance of OEP using a single IMU in daily life.
Eat-Radar: Continuous Fine-Grained Intake Gesture Detection Using FMCW Radar and 3D Temporal Convolutional Network with Attention
The results of the proposed approach indicate the feasibility of using radar for fine-grained eating and drinking gesture detection and segmentation in meal sessions.
Skeleton-Based Action Segmentation with Multi-Stage Spatial-Temporal Graph Convolutional Neural Networks
State-of-the-art action segmentation approaches use multiple stages of temporal convolutions.
Automated freezing of gait assessment with marker-based motion capture and multi-stage spatial-temporal graph convolutional neural networks
Furthermore, a novel deep neural network architecture is proposed that aims to better capture the spatial and temporal dependencies than the state-of-the-art baselines.
A multi-layered energy consumption model for smart wireless acoustic sensor networks
This model provides a first step of exploration prior to custom design of a smart wireless acoustic sensor, and also can be used to compare the energy consumption of different protocols.
