AIMC Topic: Machine Learning

Clear Filters Showing 19571 to 19580 of 34417 articles

Using Tweets to Understand How COVID-19-Related Health Beliefs Are Affected in the Age of Social Media: Twitter Data Analysis Study.

Journal of medical Internet research
BACKGROUND: The emergence of SARS-CoV-2 (ie, COVID-19) has given rise to a global pandemic affecting 215 countries and over 40 million people as of October 2020. Meanwhile, we are also experiencing an infodemic induced by the overabundance of informa...

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

PLoS computational biology
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...

Artificial intelligence supported anemia control system (AISACS) to prevent anemia in maintenance hemodialysis patients.

International journal of medical sciences
Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron supplements (ISs) are used as preventive measures, presents important difficulties for hemodialysis patients. Nevertheless, the number of physicians able to manage such medications a...

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

Frontiers in immunology
A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression,...

Intelligent Supernovae Classification Systems in the KDUST context.

Anais da Academia Brasileira de Ciencias
With the advent of large astronomical surveys plus multi-messenger astronomy, both automatic detection and classification of Type Ia supernovae have been addressed by different machine learning techniques. In this article we present three solutions a...

An evaluation of machine learning methods for speed-bump detection on a GoPro dataset.

Anais da Academia Brasileira de Ciencias
Every day, new applications arise relying on the use of high-resolution road maps in both academic and industrial environments. Autonomous vehicles rely on digital maps to navigate when optical sensors cannot be trusted, such as heavy rainfalls, snow...

Machine learning-based cytokine microarray digital immunoassay analysis.

Biosensors & bioelectronics
Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short ...

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning.

Computers in biology and medicine
BACKGROUND: Presumed serious infection (PSI) is defined as a blood culture drawn and new antibiotic course of at least 4 days among pediatric patients with Central Venous Lines (CVLs). Early PSI prediction and use of medical interventions can prevent...

Predicting Slurry Pressure Balance with a Long Short-Term Memory Recurrent Neural Network in Difficult Ground Condition.

Computational intelligence and neuroscience
The safety of tunneling with shield tunnel boring machines largely depends on the tunnel face pressure, which is currently decided by human operators empirically. Face pressure control is vulnerable to human misjudgment and human errors can cause sev...

Key Experimental Factors of Machine Learning-Based Identification of Surgery Cancellations.

Journal of healthcare engineering
This study aimed to provide effective methods for the identification of surgeries with high cancellation risk based on machine learning models and analyze the key factors that affect the identification performance. The data covered the period from Ja...