AIMC Topic: Machine Learning

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Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction.

The Journal of arthroplasty
BACKGROUND: Revision total knee arthroplasty (rTKA) and revision total hip arthroplasty (rTHA) are among the most resource-intensive orthopaedic procedures. The primary aim of this study was to compare the accuracy of machine learning models between ...

Machine learning models for acute kidney injury prediction and management: a scoping review of externally validated studies.

Critical reviews in clinical laboratory sciences
Despite advancements in medical care, acute kidney injury (AKI) remains a major contributor to adverse patient outcomes and presents a significant challenge due to its associated morbidity, mortality, and financial cost. Machine learning (ML) is incr...

SDoH Impact on Periodontal Disease Using Machine Learning and Dental Records.

Journal of dental research
The impact of social determinants of health (SDoH) on periodontal disease (PD) is critical to study, as a deeper understanding of SDoH offers significant potential to inform policy and help clinicians provide holistic patient care. The use of machine...

Selective Deployment of AI in Healthcare and the Problem of Declining Human Expertise.

Bioethics
Machine-learning algorithms are transforming healthcare diagnostics and prognostics. However, they sometimes underperform for groups underrepresented in their training data. Vandersluis and Savulescu have suggested selectively deploying these algorit...

Predicting prolonged hospitalization in asthma patients: model development and external validation.

The Journal of asthma : official journal of the Association for the Care of Asthma
PURPOSE: This study aims to develop and validate a machine learning (ML) model to predict prolonged hospitalization in asthma patients.

Coastal ozone dynamics and formation regime in Eastern China: Integrating trend decomposition and machine learning techniques.

Journal of environmental sciences (China)
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone, which are at high levels in urban China. This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to i...

Pseudotargeted metabolomics profiles potential damage-associated molecular patterns as machine learning predictors for acute pancreatitis.

Journal of pharmaceutical and biomedical analysis
Acute pancreatitis (AP) is a common gastrointestinal disease characterized by pancreatic cell damage and inflammation. Given the early clinical diagnosis and management challenges, exploring novel analytical frameworks from new orientations for inter...

Deep machine learning-assisted MOF@COF fluorescence/colorimetric dual-mode intelligent ratiometric sensing platform for sensitive glutathione detection.

Talanta
Glutathione (GSH) levels have been linked to aging and the pathogenesis of various diseases, highlighting the necessity for the development of sensitive analytical methods for GSH to facilitate disease diagnosis and treatment. In this study, we synth...

GZSL-Lite: A Lightweight Generalized Zero-Shot Learning Network for SSVEP-Based BCIs.

IEEE transactions on bio-medical engineering
Generalized zero-shot learning (GZSL) networks offer promising avenues for the development of user-friendly steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs), aiming to alleviate the training burden on users. These n...

A Novel NICU Sleep State Stratification: Multiperspective Features, Adaptive Feature Selection and Ensemble Model.

IEEE transactions on bio-medical engineering
The examination of sleep patterns in newborns, particularly premature infants, is crucial for understanding neonatal development. This study presents an automated multi-sleep state classification approach for infants in neonatal intensive care units ...