AIMC Topic: Algorithms

Clear Filters Showing 3681 to 3690 of 28713 articles

Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.

Viruses
Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time- and res...

Development of a LASSO machine learning algorithm-based model for postoperative delirium prediction in hepatectomy patients.

BMC surgery
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepatectomy.

Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machin...

Predicting drug combination side effects based on a metapath-based heterogeneous graph neural network.

BMC bioinformatics
In recent years, combined drug screening has played a very important role in modern drug discovery. Generally, synergistic drug combinations are crucial in treatment for many diseases. However, the toxic side effects of drug combinations are probably...

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus.

Scientific reports
This study sought to establish and validate an interpretable CT radiomics-based machine learning model capable of predicting post-acute pancreatitis diabetes mellitus (PPDM-A), providing clinicians with an effective predictive tool to aid patient man...

Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints.

Scientific reports
Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher accuracy and efficiency. However, the key to achieving accurate segmentation lies in abundant clues...

Artificial intelligence as a transforming factor in motility disorders-automatic detection of motility patterns in high-resolution anorectal manometry.

Scientific reports
High-resolution anorectal manometry (HR-ARM) is the gold standard for anorectal functional disorders' evaluation, despite being limited by its accessibility and complex data analysis. The London Protocol and Classification were developed to standardi...

Merging motoneuron and postural synergies in prosthetic hand design for natural bionic interfacing.

Science robotics
Despite the advances in bionic reconstruction of missing limbs, the control of robotic limbs is still limited and, in most cases, not felt to be as natural by users. In this study, we introduce a control approach that combines robotic design based on...

Novel approach for quality control testing of medical displays using deep learning technology.

Biomedical physics & engineering express
In digital image diagnosis using medical displays, it is crucial to rigorously manage display devices to ensure appropriate image quality and diagnostic safety. The aim of this study was to develop a model for the efficient quality control (QC) of me...