AIMC Topic: Machine Learning

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Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model.

BMC pregnancy and childbirth
OBJECTIVE: The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery.

A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults.

BMC geriatrics
BACKGROUND: Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk fac...

Flexible Patched Brain Transformer model for EEG decoding.

Scientific reports
Decoding the human brain using non-invasive methods is a significant challenge. This study aims to enhance electroencephalography (EEG) decoding by developing of machine learning methods. Specifically, we propose the novel, attention-based Patched Br...

Machine learning-based risk prediction model for arteriovenous fistula stenosis.

European journal of medical research
BACKGROUND: Arteriovenous fistula stenosis is a common complication in hemodialysis patients, yet effective predictive tools are lacking. This study aims to develop an interpretable machine learning model for stenosis risk prediction.

Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms.

Scientific reports
Microorganisms are one of the most promising biomarkers for cancer, and the relationship between microorganisms and lung cancer occurrence and development provides significant potential for pulmonary nodule (PN) diagnosis from a microbiological persp...

Combination of exhaled volatile organic compounds with serum biomarkers predicts respiratory infection severity.

Pulmonology
OBJECTIVE: During respiratory infections, host-pathogen interaction alters metabolism, leading to changes in the composition of expired volatile organic compounds (VOCs) and soluble immunomodulators. This study aims to identify VOC and blood biomarke...

Calibrating the prediction model of soluble solids content and firmness in kiwifruit across years based on NIR spectroscopy using model transfer and transfer learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Near-infrared (NIR) spectroscopy has been widely used in nondestructive detection of fruit internal quality. However, the biological variability of fruit would change their texture, which may lead to the failure of fruit quality prediction models bui...

Machine learning-combined hyperspectral imaging analysis for the non-destructive identification of wheat flours with varying gluten strengths.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study aimed to non-destructively identify wheat flours with different gluten strengths through the application of machine learning-combined hyperspectral imaging analysis. The performance of this approach was compared to conventional instrumenta...

International external validation of the SORG machine learning algorithm for predicting sustained postoperative opioid prescription after anterior cervical discectomy and fusion using a Taiwanese cohort of 1,037 patients.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Anterior cervical discectomy and fusion (ACDF) is widely performed for cervical spine disorders, with opioids commonly prescribed postoperatively for pain management. However, prolonged opioid use carries significant risks such as...

Are we underestimating the driving factors and potential risks of freshwater microplastics from in situ and in silico perspective?

Water research
The high loads of heterogeneous microplastics (MPs) in water system sparked the exploration of MPs source and impact in the environment. However, the contributions of driving factors to MPs contamination and the potential risks posed by multidimensio...