AIMC Topic: Humans

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Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics.

Critical reviews in clinical laboratory sciences
Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately overtakes the existing market. Typically, when disruptive innovations are introduced, their performa...

Representation learning of resting state fMRI with variational autoencoder.

NeuroImage
Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rsfMRI data. Here we establish a variational auto-encoder, as a generative model ...

Use of Machine Learning for the Estimation of Down- and Up-Link Field Exposure in Multi-Source Indoor WiFi Scenarios.

Bioelectromagnetics
A novel Machine Learning (ML) method based on Neural Networks (NN) is proposed to assess radio-frequency (RF) exposure generated by WiFi sources in indoor scenarios. The aim was to build an NN capable of addressing the complexity and variability of r...

Logistic matrix factorisation and generative adversarial neural network-based method for predicting drug-target interactions.

Molecular diversity
Identifying drug-target protein association pairs is a prerequisite and a crucial task in drug discovery and development. Numerous computational models, based on different assumptions and algorithms, have been proposed as an alternative to the labori...

Electrocardiogram-Based Emotion Recognition Systems and Their Applications in Healthcare-A Review.

Sensors (Basel, Switzerland)
Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that...

Deep Learning for Efficient and Optimal Motion Planning for AUVs with Disturbances.

Sensors (Basel, Switzerland)
We use the recent advances in Deep Learning to solve an underwater motion planning problem by making use of optimal control tools-namely, we propose using the Deep Galerkin Method (DGM) to approximate the Hamilton-Jacobi-Bellman PDE that can be used ...

Crack Size Identification for Bearings Using an Adaptive Digital Twin.

Sensors (Basel, Switzerland)
In this research, the aim is to investigate an adaptive digital twin algorithm for fault diagnosis and crack size identification in bearings. The main contribution of this research is to design an adaptive digital twin (ADT). The design of the ADT te...

A Small World Graph Approach for an Efficient Indoor Positioning System.

Sensors (Basel, Switzerland)
The main goal of an Indoor Positioning System (IPS) is to estimate the position of mobile devices in indoor environments. For this purpose, the primary source of information is the signal strength of packets received by a set of routers. The fingerpr...

A Time-Series-Based New Behavior Trace Model for Crowd Workers That Ensures Quality Annotation.

Sensors (Basel, Switzerland)
Crowdsourcing is a new mode of value creation in which organizations leverage numerous Internet users to accomplish tasks. However, because these workers have different backgrounds and intentions, crowdsourcing suffers from quality concerns. In the l...

Rebirth of Distributed AI-A Review of eHealth Research.

Sensors (Basel, Switzerland)
The envisioned smart city domains are expected to rely heavily on artificial intelligence and machine learning (ML) approaches for their operations, where the basic ingredient is data. Privacy of the data and training time have been major roadblocks ...