AIMC Topic: Deep Learning

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U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging.

Computers in biology and medicine
With the increasing prevalence of machine learning in critical fields like healthcare, ensuring the safety and reliability of these systems is crucial. Estimating uncertainty plays a vital role in enhancing reliability by identifying areas of high an...

An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks.

Biomolecules
(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing radiation therapy, which can result in morbidity and even death. However, a notable deficiency exists in the availability of specific drugs designed f...

Performance evaluation of a deep learning model for automatic detection and localization of idiopathic osteosclerosis on dental panoramic radiographs.

Scientific reports
Idiopathic osteosclerosis (IO) are focal radiopacities of unknown etiology observed in the jaws. These radiopacities are incidentally detected on dental panoramic radiographs taken for other reasons. In this study, we investigated the performance of ...

A new computer-aided diagnosis tool based on deep learning methods for automatic detection of retinal disorders from OCT images.

International ophthalmology
PURPOSE: Early detection of retinal disorders using optical coherence tomography (OCT) images can prevent vision loss. Since manual screening can be time-consuming, tedious, and fallible, we present a reliable computer-aided diagnosis (CAD) software ...

A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.

Scientific data
High-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefa...

A novel deep learning-based method for automatic stereology of microglia cells from low magnification images.

Neurotoxicology and teratology
Microglial cells mediate diverse homeostatic, inflammatory, and immune processes during normal development and in response to cytotoxic challenges. During these functional activities, microglial cells undergo distinct numerical and morphological chan...

A topological deep learning framework for neural spike decoding.

Biophysical journal
The brain's spatial orientation system uses different neuron ensembles to aid in environment-based navigation. Two of the ways brains encode spatial information are through head direction cells and grid cells. Brains use head direction cells to deter...

Deep learning for automatic bowel-obstruction identification on abdominal CT.

European radiology
RATIONALE AND OBJECTIVES: Automated evaluation of abdominal computed tomography (CT) scans should help radiologists manage their massive workloads, thereby leading to earlier diagnoses and better patient outcomes. Our objective was to develop a machi...

Sensor-based characterization of construction and demolition waste at high occupancy densities using synthetic training data and deep learning.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Sensor-based monitoring of construction and demolition waste (CDW) streams plays an important role in recycling (RC). Extracted knowledge about the composition of a material stream helps identifying RC paths, optimizing processing plants and form the...