AIMC Topic: Machine Learning

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Unveiling the potential of machine learning approaches in predicting the emergence of stroke at its onset: a predicting framework.

Scientific reports
A stroke is a dangerous, life-threatening disease that mostly affects people over 65, but an unhealthy diet is also contributing to the development of strokes at younger ages. Strokes can be treated successfully if they are identified early enough, a...

Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online.

Nature communications
Given the profound societal impact of conspiracy theories, probing the psychological factors associated with their spread is paramount. Most research lacks large-scale behavioral outcomes, leaving factors related to actual online support for conspira...

A machine learning-based electronic nose system using numerous low-cost gas sensors for real-time alcoholic beverage classification.

Analytical methods : advancing methods and applications
This study introduces numerous low-cost gas sensors and a real-time alcoholic beverage classification system based on machine learning. Dogs possess a superior sense of smell compared to humans due to having 30 times more olfactory receptors and thre...

Obesity prediction: Novel machine learning insights into waist circumference accuracy.

Diabetes & metabolic syndrome
AIMS: This study aims to enhance the precision of obesity risk assessments by improving the accuracy of waist circumference predictions using machine learning techniques.

AI-assisted assessment and treatment of aphasia: a review.

Frontiers in public health
Aphasia is a language disorder caused by brain injury that often results in difficulties with speech production and comprehension, significantly impacting the affected individuals' lives. Recently, artificial intelligence (AI) has been advancing in m...

Radiomics-based machine learning model to phenotype hip involvement in ankylosing spondylitis: a pilot study.

Frontiers in immunology
OBJECTIVES: Hip involvement is an important reason of disability in patients with ankylosing spondylitis (AS). Unveiling the potential phenotype of hip involvement in AS remains an unmet need to understand its biological mechanisms and improve clinic...

Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy.

Frontiers in immunology
BACKGROUND: Cancer stem cells (CSCs) are a subset of cells within tumors that possess the unique ability to self-renew and give rise to diverse tumor cells. These cells are crucial in driving tumor metastasis, recurrence, and resistance to treatment....

From data to decision: Machine learning determination of aerobic and anaerobic thresholds in athletes.

PloS one
Lactate analysis plays an important role in sports science and training decisions for optimising performance, endurance, and overall success in sports. Two parameters are widely used for these goals: aerobic (AeT) and anaerobic (AnT) thresholds. Howe...

Computer-aided diagnosis of eyelid skin tumors using machine learning.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To develop an automated, new framework based on machine learning to diagnose malignant eyelid skin tumors.

Applications of Machine Learning in Meniere's Disease Assessment Based on Pure-Tone Audiometry.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: To apply machine learning models based on air conduction thresholds of pure-tone audiometry for automatic diagnosis of Meniere's disease (MD) and prediction of endolymphatic hydrops (EH).