AIMC Topic: Humans

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Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.

Molecular diversity
Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can le...

Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) by wearable sensor devices embedded in the Internet of things (IOT) can play a significant role in remote health monitoring and emergency notification to provide healthcare of higher standards. The purpose of this stu...

Driving Behaviour Analysis Using Machine and Deep Learning Methods for Continuous Streams of Vehicular Data.

Sensors (Basel, Switzerland)
In the last few decades, vehicles are equipped with a plethora of sensors which can provide useful measurements and diagnostics for both the vehicle's condition as well as the driver's behaviour. Furthermore, the rapid increase for transportation nee...

An Integrated Compensation Method for the Force Disturbance of a Six-Axis Force Sensor in Complex Manufacturing Scenarios.

Sensors (Basel, Switzerland)
As one of the key components for active compliance control and human-robot collaboration, a six-axis force sensor is often used for a robot to obtain contact forces. However, a significant problem is the distortion between the contact forces and the ...

Efficient Source Camera Identification with Diversity-Enhanced Patch Selection and Deep Residual Prediction.

Sensors (Basel, Switzerland)
Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed based on studying the traces left upon shooting, several deep-learning-based methods have also emerg...

Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.

Scientific reports
Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 in resource-scarce countries. In this study, we applied machine learning (ML) to the task of detection of SARS-CoV-2 infection using basic laboratory ...

A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions.

Nature communications
Deep learning algorithms trained on instances that violate the assumption of being independent and identically distributed (i.i.d.) are known to experience destructive interference, a phenomenon characterized by a degradation in performance. Such a v...

An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation.

Nature communications
We propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by providing faster convergence, higher accuracy and a flexible long short-term memory. We...

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence.

BMJ open
INTRODUCTION: The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were both published to improve the reporting and criti...

Aggregation-and-Attention Network for brain tumor segmentation.

BMC medical imaging
BACKGROUND: Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted d...