AIMC Topic: Algorithms

Clear Filters Showing 20701 to 20710 of 28713 articles

Automated deep-neural-network surveillance of cranial images for acute neurologic events.

Nature medicine
Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function-'time is brain'. Although these disorders are often recognizabl...

DeepSort: deep convolutional networks for sorting haploid maize seeds.

BMC bioinformatics
BACKGROUND: Maize is a leading crop in the modern agricultural industry that accounts for more than 40% grain production worldwide. THe double haploid technique that uses fewer breeding generations for generating a maize line has accelerated the pace...

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.

BMC bioinformatics
BACKGROUND: The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors were more associated with the DR than others. If we can detect the DR related risk factors more acc...

Adaptive non-negative projective semi-supervised learning for inductive classification.

Neural networks : the official journal of the International Neural Network Society
We discuss the inductive classification problem by proposing a joint framework termed Adaptive Non-negative Projective Semi-Supervised Learning (ANP-SSL). Specifically, ANP-SSL integrates the adaptive inductive label propagation, adaptive reconstruct...

Evaluation of machine learning techniques with multiple remote sensing datasets in estimating monthly concentrations of ground-level PM.

Environmental pollution (Barking, Essex : 1987)
Fine particulate matter (PM) has been recognized as a key air pollutant that can influence population health risk, especially during extreme cases such as wildfires. Previous studies have applied geospatial techniques such as land use regression to m...

A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.

Molecules (Basel, Switzerland)
Research on cytokine recognition is of great significance in the medical field due to the fact cytokines benefit the diagnosis and treatment of diseases, but the current methods for cytokine recognition have many shortcomings, such as low sensitivity...

Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning.

IEEE transactions on medical imaging
In portable, 3-D, and ultra-fast ultrasound imaging systems, there is an increasing demand for the reconstruction of high-quality images from a limited number of radio-frequency (RF) measurements due to receiver (Rx) or transmit (Xmit) event sub-samp...

FissureNet: A Deep Learning Approach For Pulmonary Fissure Detection in CT Images.

IEEE transactions on medical imaging
Pulmonary fissure detection in computed tomography (CT) is a critical component for automatic lobar segmentation. The majority of fissure detection methods use feature descriptors that are hand-crafted, low-level, and have local spatial extent. The d...

Using Machine Learning to Aid the Interpretation of Urine Steroid Profiles.

Clinical chemistry
BACKGROUND: Urine steroid profiles are used in clinical practice for the diagnosis and monitoring of disorders of steroidogenesis and adrenal pathologies. Machine learning (ML) algorithms are powerful computational tools used extensively for the reco...