AIMC Topic: Machine Learning

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Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.

Pediatric surgery international
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...

Prognostic predictions in psychosis: exploring the complementary role of machine learning models.

BMJ mental health
BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine learning (ML) shows promise in outcome prediction, it has not yet been integrated into clinical practi...

Machine learning-based optimization of biogas and methane yields in UASB reactors for treating domestic wastewater.

Biodegradation
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...

From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.

World journal of urology
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...

Leveraging transfer learning for efficient bioprinting.

Biofabrication
Bioprinting is a promising family of processes combining 3D printing with life sciences, offering the potential to significantly advance various applications. Despite numerous research efforts aimed at enhancing process modeling, optimizing capabilit...

A comparative study of fully automatic and semi-automatic methods for oil spill detection using Sentinel-1 data.

Environmental monitoring and assessment
The oil spill detection and assessment study conducted in the Banten Province of Indonesia involves the application of Sentinel-1 satellite data and machine learning tools in the year 2024. Synthetic Aperture Radar (SAR) data were used with VV polari...

The class imbalance problem in automatic localization of the epileptogenic zone for epilepsy surgery: a systematic review.

Journal of neural engineering
Accurate localization of the epileptogenic zone (EZ) is crucial for epilepsy surgery, but the class imbalance of epileptogenic vs. non-epileptogenic electrode contacts in intracranial electroencephalography (iEEG) data poses significant challenges fo...

Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection.

PloS one
Around 1.5 million new cases of Hepatitis C Virus (HCV) are diagnosed globally each year (World Health Organization, 2023). Consequently, there is a pressing need for early diagnostic methods for HCV. This study investigates the prognostic accuracy o...

Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology.

PloS one
BACKGROUND: Brominated flame retardants (BFRs) are classified as important endocrine disruptors and persistent organic pollutants; nevertheless, there is no comprehensive investigation to evaluate the association between BFRs and hyperuricemia, and t...

Adaptive DDoS detection mode in software-defined SIP-VoIP using transfer learning with boosted meta-learner.

PloS one
The Internet has continued to provision its infrastructure as a platform for competitive marketing, enhanced productivity, and monetization efficacy. However, it has become a means for adversaries to exploit unsuspecting users and, in turn, compromis...