AIMC Topic: Machine Learning

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Improving SDG Classification Precision Using Combinatorial Fusion.

Sensors (Basel, Switzerland)
Combinatorial fusion algorithm (CFA) is a machine learning and artificial intelligence (ML/AI) framework for combining multiple scoring systems using the rank-score characteristic (RSC) function and cognitive diversity (CD). When measuring the releva...

Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

Parasites & vectors
BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it can cause severe clinical signs such as hemolytic anemia. Apart from acute clinical symptoms dogs c...

The Design of Adolescents' Physical Health Prediction System Based on Deep Reinforcement Learning.

Computational intelligence and neuroscience
According to the general recognition in the first half of the last century, hypertension was not considered a kind of disease, but was regarded as a compensatory response commonly seen in the elderly, and it would not occur to younger people. Because...

Use of machine learning to model surgical decision-making in lumbar spine surgery.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: The majority of lumbar spine surgery referrals do not proceed to surgery. Early identification of surgical candidates in the referral process could expedite their care, whilst allowing timelier implementation of non-operative strategies for ...

Exploring the use of machine learning for the assessment of skeletal fracture morphology and differentiation between impact mechanisms: A pilot study.

Journal of forensic sciences
Analyzing and interpreting traumatic injuries is a fundamental aspect of routine forensic case work. As the human skeleton can be impacted through a combination of loading mechanisms and varying impact energies, the analysis and interpretation of ske...

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while ...

A Survey of Blind Modulation Classification Techniques for OFDM Signals.

Sensors (Basel, Switzerland)
Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communic...

Age Classification in Forensic Medicine Using Machine Learning Techniques.

Sovremennye tekhnologii v meditsine
UNLABELLED: was to assess the capabilities of age determination (age group) at death using classification techniques by histomorphometric characteristics of osseous and cartilaginous tissue aging.

Artificial intelligence and spine imaging: limitations, regulatory issues and future direction.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
BACKGROUND: As big data and artificial intelligence (AI) in spine care, and medicine as a whole, continue to be at the forefront of research, careful consideration to the quality and techniques utilized is necessary. Predictive modeling, data science...

Potential Application of Machine-Learning-Based Quantum Chemical Methods in Environmental Chemistry.

Environmental science & technology
It is an important topic in environmental sciences to understand the behavior and toxicology of chemical pollutants. Quantum chemical methodologies have served as useful tools for probing behavior and toxicology of chemical pollutants in recent decad...