AIMC Topic: Machine Learning

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In Silico Modeling of Fabry Disease Pathophysiology for the Identification of Early Cellular Damage Biomarker Candidates.

International journal of molecular sciences Sep 25, 2024
Fabry disease (FD) is an X-linked lysosomal disease whose ultimate consequences are the accumulation of sphingolipids and subsequent inflammatory events, mainly at the endothelial level. The outcomes include different nervous system manifestations as...
Lamin Type A Fabry Disease Biomarkers Computer Simulation Protein Serine-Threonine Kinases Humans Machine Learning
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Predicting Outcomes of Preterm Neonates Post Intraventricular Hemorrhage.

International journal of molecular sciences Sep 25, 2024
Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorrhagic ventricular dilatation (PHVD), a severe complication that can impact survival and long-term outcomes. Early detection of PHVD before clinical on...
Machine Learning Prospective Studies Biomarkers Prognosis Female Infant, Newborn Humans Cerebral Hemorrhage Infant, Premature Male Proteomics Longitudinal Studies
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Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

Journal for immunotherapy of cancer Sep 25, 2024
Phenylurea Compounds Quinolines Male Middle Aged Liver Neoplasms Carcinoma, Hepatocellular Immune Checkpoint Inhibitors Antineoplastic Combined Chemotherapy Protocols Female Aged Humans Radiomics Machine Learning Tomography, X-Ray Computed
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Integrating Social Determinants of Health in Machine Learning-Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study.

JMIR research protocols Sep 25, 2024
BACKGROUND: The use of both clinical factors and social determinants of health (SDoH) in referral decision-making for case management may improve optimal use of resources and reduce outcome disparities among patients with diabetes.
Humans Machine Learning Diabetes Mellitus Social Determinants of Health Case Management Middle Aged Decision Support Systems, Clinical United States Decision Support Techniques Female Male
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Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

PloS one Sep 25, 2024
BACKGROUND: Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as it can be used to estimate the coagulation zone of microwave ablation.
Animals Liver Neoplasms Machine Learning Swine Liver Algorithms Ablation Techniques Microwaves Temperature Ultrasonography
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Subject-Independent Wearable P300 Brain-Computer Interface Based on Convolutional Neural Network and Metric Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 25, 2024
The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user experience of the system. Each user needs to spend additional time establishing a decoder adapted to their own brainwaves. Therefore, achieving subje...
Young Adult Adult Male Brain-Computer Interfaces Wearable Electronic Devices Humans Machine Learning Event-Related Potentials, P300 Algorithms Neural Networks, Computer Electroencephalography Female Calibration
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Editorial Commentary: Machine Learning and Artificial Intelligence Are Valuable Tools yet Dependent on the Data Input.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association Sep 24, 2024
Machine learning is likely to become one of the most valuable tools for predicting outcomes in patients with patellofemoral instability. Traditional statistical analysis is challenging in this diagnosis as the result of the multitude of risk factors....
Humans Artificial Intelligence Machine Learning Joint Instability
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A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples.

Clinica chimica acta; international journal of clinical chemistry Sep 24, 2024
BACKGROUND: Neonatal sepsis is a global health threat, contributing to high morbidity and mortality rates among newborns. Recognizing the profound impact of neonatal sepsis on long-term health outcomes emphasizes the critical need for timely detectio...
Machine Learning Biomarkers Infant, Newborn Humans Neonatal Sepsis Electronic Nose Feces Gas Chromatography-Mass Spectrometry Volatile Organic Compounds
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Multiplexed bacterial recognition based on "All-in-One" semiconducting polymer dots sensor and machine learning.

Talanta Sep 24, 2024
The accurate discrimination of bacterial infection is imperative for precise clinical diagnosis and treatment. Here, this work presents a simplified sensor array utilizing "All-in-One" Pdots for efficient discrimination of diverse bacterial samples. ...
Biofilms Semiconductors Biosensing Techniques Machine Learning Fluorescence Resonance Energy Transfer Quantum Dots Bacteria Polymers
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Artificial Intelligence to Predict Billing Code Levels of Emergency Department Encounters.

Annals of emergency medicine Sep 24, 2024
STUDY OBJECTIVE: To use artificial intelligence (AI) to predict billing code levels for emergency department (ED) encounters.
Middle Aged ROC Curve Natural Language Processing Humans Female Artificial Intelligence Adult Machine Learning Male Emergency Service, Hospital Clinical Coding Current Procedural Terminology
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