AIMC Topic: Classification Algorithms

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Machine learning models and classification algorithms in the diagnosis of vestibular migraine: A systematic review and meta-analysis.

Headache Mar 13, 2025
OBJECTIVES: To perform a systematic review and meta-analysis to evaluate the effectiveness of machine learning (ML) algorithms in the diagnosis of vestibular migraine.
Machine Learning Algorithms Vestibular Diseases Classification Algorithms Migraine Disorders Humans
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An effective COVID-19 classification in X-ray images using a new deep learning framework.

Journal of X-ray science and technology Jan 19, 2025
BackgroundThe global concern regarding the diagnosis of lung-related diseases has intensified due to the rapid transmission of coronavirus disease 2019 (COVID-19). Artificial Intelligence (AI) based methods are emerging technologies that help to iden...
Radiography, Thoracic Classification Algorithms Humans COVID-19 Deep Learning
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Classification algorithms trained on simple (symmetric) lifting data perform poorly in predicting hand loads during complex (free-dynamic) lifting tasks.

Applied ergonomics Dec 10, 2024
The performance of machine learning (ML) algorithms is dependent on which dataset it has been trained on. While ML algorithms are increasingly used for lift risk assessment, many algorithms are often trained and tested on controlled simulation datase...
Task Performance and Analysis Young Adult Weight-Bearing Adult Algorithms Biomechanical Phenomena Hand Lifting Male Humans Female Electromyography Classification Algorithms Posture Machine Learning
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Towards robust multimodal ultrasound classification for liver tumor diagnosis: A generative approach to modality missingness.

Computer methods and programs in biomedicine Jun 1, 2025
BACKGROUND AND OBJECTIVE: In medical image analysis, combining multiple imaging modalities enhances diagnostic accuracy by providing complementary information. However, missing modalities are common in clinical settings, limiting the effectiveness of...
Classification Algorithms Image Interpretation, Computer-Assisted Predictive Learning Models Liver Neoplasms Image Processing, Computer-Assisted Area Under Curve Multimodal Imaging Female Humans Data Accuracy Male Ultrasonography
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External validation of a machine learning-based classification algorithm for ambulatory heart rhythm diagnostics in pericardioversion atrial fibrillation patients using smartphone photoplethysmography: the SMARTBEATS-ALGO study.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Mar 28, 2025
AIMS: The aim of this study was to perform an external validation of an automatic machine learning (ML) algorithm for heart rhythm diagnostics using smartphone photoplethysmography (PPG) recorded by patients with atrial fibrillation (AF) and atrial f...
Algorithms Female Humans Machine Learning Male Middle Aged Smartphone Reproducibility of Results Aged Classification Algorithms Predictive Value of Tests Signal Processing, Computer-Assisted Electric Countershock Atrial Fibrillation Atrial Flutter Heart Rate Electrocardiography Mobile Applications Electrocardiography, Ambulatory Support Vector Machine Photoplethysmography
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[Research on arrhythmia classification algorithm based on adaptive multi-feature fusion network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2025
Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia feature...
Algorithms Deep Learning Signal Processing, Computer-Assisted Arrhythmias, Cardiac Electrocardiography Humans Neural Networks, Computer Classification Algorithms
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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.

PloS one Jan 1, 2025
CONTEXT AND BACKGROUND: Depression has affected millions of people worldwide and has become one of the most common mental disorders. Early mental disorder detection can reduce costs for public health agencies and prevent other major comorbidities. Ad...
Humans Stress Disorders, Post-Traumatic Machine Learning Natural Language Processing Algorithms Classification Algorithms Depression
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