AIMC Topic: Reproducibility of Results

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M1M2: Deep-Learning-Based Real-Time Emotion Recognition from Neural Activity.

Sensors (Basel, Switzerland)
Emotion recognition, or the ability of computers to interpret people's emotional states, is a very active research area with vast applications to improve people's lives. However, most image-based emotion recognition techniques are flawed, as humans c...

Gait Trajectory Prediction on an Embedded Microcontroller Using Deep Learning.

Sensors (Basel, Switzerland)
Achieving a normal gait trajectory for an amputee's active prosthesis is challenging due to its kinematic complexity. Accordingly, lower limb gait trajectory kinematics and gait phase segmentation are essential parameters in controlling an active pro...

Mapping of groundwater salinization and modelling using meta-heuristic algorithms for the coastal aquifer of eastern Saudi Arabia.

The Science of the total environment
The growing increase in groundwater (GW) salinization in the coastal aquifers has reached an alarming socio-economic menace in Saudi Arabia and various places globally due to several natural and anthropogenic activities. Hence, evaluating the GW sali...

An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching.

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic engineering and artificial intelligence demands hardware elements that emulates synapse algorithms. During the last decade electrolyte-gated organic conjugated materials have been explored as a platform for artificial synapses for neurom...

Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison.

BMC medical research methodology
BACKGROUND: There is growing enthusiasm for the application of machine learning (ML) and artificial intelligence (AI) techniques to clinical research and practice. However, instructions on how to develop robust high-quality ML and AI in medicine are ...

Identification of Bacterial Pathogens at Genus and Species Levels through Combination of Raman Spectrometry and Deep-Learning Algorithms.

Microbiology spectrum
The rapid and accurate identification of the causing agents during bacterial infections would greatly improve pathogen transmission, prevention, patient care, and medical treatments in clinical settings. Although many conventional and molecular metho...

Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning.

Sensors (Basel, Switzerland)
Advances in neural networks have garnered growing interest in applications of machine vision in livestock management, but simpler landmark-based approaches suitable for small, early stage exploratory studies still represent a critical stepping stone ...

A Machine Learning Approach for Recommending Herbal Formulae with Enhanced Interpretability and Applicability.

Biomolecules
Herbal formulae (HFs) are representative interventions in Korean medicine (KM) for the prevention and treatment of various diseases. Here, we proposed a machine learning-based approach for HF recommendation with enhanced interpretability and applicab...

Artificial intelligence-based algorithm for cervical vertebrae maturation stage assessment.

Orthodontics & craniofacial research
OBJECTIVE: The aim of this study was to develop an artificial intelligence (AI) algorithm to automatically and accurately determine the stage of cervical vertebra maturation (CVM) with the main purpose being to eliminate the human error factor.