AI Medical Compendium Topic

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Recognition, Psychology

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Emotional Climate Recognition in Conversations using Peers' Speech-based Bispectral Features and Affect Dynamics.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Emotion recognition in conversations using artificial intelligence (AI) has recently gained a lot of attention, as it can provide additional emotion cues that can be correlated with human social behavior. An extension towards an AI-based emotional cl...

Overcoming Data Scarcity in Human Activity Recognition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Wearable sensors have become increasingly popular in recent years, with technological advances leading to cheaper, more widely available, and smaller devices. As a result, there has been a growing interest in applying machine learning techniques for ...

Enhancing robustness in video recognition models: Sparse adversarial attacks and beyond.

Neural networks : the official journal of the International Neural Network Society
Recent years have witnessed increasing interest in adversarial attacks on images, while adversarial video attacks have seldom been explored. In this paper, we propose a sparse adversarial attack strategy on videos (DeepSAVA). Our model aims to add a ...

Hierarchical attention-guided multiscale aggregation network for infrared small target detection.

Neural networks : the official journal of the International Neural Network Society
All man-made flying objects in the sky, ships in the ocean can be regarded as small infrared targets, and the method of tracking them has been received widespread attention in recent years. In search of a further efficient method for infrared small t...

Detection of Medication Mentions and Medication Change Events in Clinical Notes Using Transformer-Based Models.

Studies in health technology and informatics
In this paper, we address the related tasks of medication extraction, event classification, and context classification from clinical text. The data for the tasks were obtained from the National Natural Language Processing (NLP) Clinical Challenges (n...

Rule-Based Natural Language Processing Pipeline to Detect Medication-Related Named Entities: Insights for Transfer Learning.

Studies in health technology and informatics
We document the procedure and performance of a rule-based NLP system that, using transfer learning, automatically extracts essential named entities related to drug errors from Japanese free-text incident reports. Subsequently, we used the rule-based ...

Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities.

Sensors (Basel, Switzerland)
In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff-to-patient ass...

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine.

Journal of visualized experiments : JoVE
In this paper, the directional gradient histogram technology is employed to extract the features of concrete image samples captured under different vibration states. The support vector machine (SVM) is utilized to learn the relationship between image...

Persons or data points? Ethics, artificial intelligence, and the participatory turn in mental health research.

The American psychologist
This article identifies and examines a tension in mental health researchers' growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition o...

Human Visual Cortex and Deep Convolutional Neural Network Care Deeply about Object Background.

Journal of cognitive neuroscience
Deep convolutional neural networks (DCNNs) are able to partially predict brain activity during object categorization tasks, but factors contributing to this predictive power are not fully understood. Our study aimed to investigate the factors contrib...