AIMC Topic: Support Vector Machine

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Examination of the relationship between D-amino acid profiles and cognitive function in individuals with mild cognitive impairment: a machine learning approach.

The international journal of neuropsychopharmacology
BACKGROUND: The global prevalence of dementia is significantly increasing. Early detection and prevention strategies, particularly for mild cognitive impairment (MCI), are crucial but currently hindered by the lack of established biomarkers. Here, we...

Automated Fall Detection in Smart Homes Using Multiple Radars and Machine Learning Classifiers.

Studies in health technology and informatics
Falls pose a significant risk, especially among elderly persons. Recently, radar sensors have been explored for fall detection. In this study, an attempt has been made to classify fall detection using multiple radars, machine learning (ML) classifier...

Automated identification of fall-related injuries in unstructured clinical notes.

American journal of epidemiology
Fall-related injuries (FRIs) are a major cause of hospitalizations among older patients, but identifying them in unstructured clinical notes poses challenges for large-scale research. In this study, we developed and evaluated natural language process...

Utilizing Machine Learning to Predict Liver Allograft Fibrosis by Leveraging Clinical and Imaging Data.

Clinical transplantation
BACKGROUND AND AIM: Liver transplant (LT) recipients may succumb to graft-related pathologies, contributing to graft fibrosis (GF). Current methods to diagnose GF are limited, ranging from procedural-related complications to low accuracy. With recent...

A Framework for Comparison and Interpretation of Machine Learning Classifiers to Predict Autism on the ABIDE Dataset.

Human brain mapping
Autism is a neurodevelopmental condition affecting ~1% of the population. Recently, machine learning models have been trained to classify participants with autism using their neuroimaging features, though the performance of these models varies in the...

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
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...

Development of a deep learning-based model to evaluate changes during radiotherapy using cervical cancer digital pathology.

Journal of radiation research
This study aims to create a deep learning-based classification model for cervical cancer biopsy before and during radiotherapy, visualize the results on whole slide images (WSIs), and explore the clinical significance of obtained features. This study...

Exploring Ovarian Cancer Prediction Models and Potential Markers Using Machine Learning.

Annals of clinical and laboratory science
OBJECTIVE: To develop machine learning models, facilitate a more accurate diagnosis of ovarian cancer (OC), and explore potential markers.

Classification of Bryde's whale individuals using high-resolution time-frequency transforms and support vector machines.

The Journal of the Acoustical Society of America
Whales generate vocalizations which may, deliberately or not, encode caller identity cues. In this study, we analyze calls produced by Bryde's whales and recorded by ocean-bottom arrays of hydrophones deployed close to the Costa Rica Rift in the Pana...

Using gut microbiome metagenomic hypervariable features for diabetes screening and typing through supervised machine learning.

Microbial genomics
Diabetes mellitus is a complex metabolic disorder and one of the fastest-growing global public health concerns. The gut microbiota is implicated in the pathophysiology of various diseases, including diabetes. This study utilized 16S rRNA metagenomic ...