AIMC Topic: Neural Networks, Computer

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What's in a trauma? Using machine learning to unpack what makes an event traumatic.

Journal of affective disorders
What differentiates a trauma from an event that is merely upsetting? Wildly different definitions of trauma have been used in both formal (psychiatric) and informal (cultural, colloquial) settings. Yet there is a dearth of empirical work examining th...

Deep reinforcement learning in medical imaging: A literature review.

Medical image analysis
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which learns a sequence of actions that maximizes the expected reward, with the representative power of deep neural networks. Recent works have demonstrated the great po...

DeepSperm: A robust and real-time bull sperm-cell detection in densely populated semen videos.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Object detection is a primary research interest in computer vision. Sperm-cell detection in a densely populated bull semen microscopic observation video presents challenges that are more difficult than those presented by oth...

Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search.

European journal of radiology
PURPOSE: To utilize a neural architecture search (NAS) approach to develop a convolutional neural network (CNN) method for distinguishing benign and malignant lesions on breast cone-beam CT (BCBCT).

Interpretability of time-series deep learning models: A study in cardiovascular patients admitted to Intensive care unit.

Journal of biomedical informatics
Interpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation of an attention layer for L...

EEG-Based Emotion Recognition by Convolutional Neural Network with Multi-Scale Kernels.

Sensors (Basel, Switzerland)
Besides facial or gesture-based emotion recognition, Electroencephalogram (EEG) data have been drawing attention thanks to their capability in countering the effect of deceptive external expressions of humans, like faces or speeches. Emotion recognit...

A Study of Deep Learning-Based Face Recognition Models for Sibling Identification.

Sensors (Basel, Switzerland)
Accurate identification of siblings through face recognition is a challenging task. This is predominantly because of the high degree of similarities among the faces of siblings. In this study, we investigate the use of state-of-the-art deep learning ...

2D-3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks.

Scientific reports
The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 10...

Interpretable and Lightweight 3-D Deep Learning Model for Automated ACL Diagnosis.

IEEE journal of biomedical and health informatics
We propose an interpretable and lightweight 3D deep neural network model that diagnoses anterior cruciate ligament (ACL) tears from a knee MRI exam. Previous works focused primarily on achieving better diagnostic accuracy but paid less attention to p...