AIMC Topic: Humans

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Deep regression neural networks for collateral imaging from dynamic susceptibility contrast-enhanced magnetic resonance perfusion in acute ischemic stroke.

International journal of computer assisted radiology and surgery
PURPOSE: Acute ischemic stroke is one of the primary causes of death worldwide. Recent studies have shown that the assessment of collateral status could aid in improving the treatment for patients with acute ischemic stroke. We present a 3D deep regr...

Cortical Tracking of Surprisal during Continuous Speech Comprehension.

Journal of cognitive neuroscience
Speech comprehension requires rapid online processing of a continuous acoustic signal to extract structure and meaning. Previous studies on sentence comprehension have found neural correlates of the predictability of a word given its context, as well...

How many models/atlases are needed as priors for capturing anatomic population variations?

Medical image analysis
Many medical image processing and analysis operations can benefit a great deal from prior information encoded in the form of models/atlases to capture variations over a population in form, shape, anatomic layout, and image appearance of objects. Howe...

Estimation of wave reflection in aorta from radial pulse waveform by artificial neural network: a numerical study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Wave reflection in aorta has been shown to have incremental value for predicting cardiovascular events. However, its estimation by wave separation analysis (WSA) is complex.

Development of an automatic muscle atrophy measuring algorithm to calculate the ratio of supraspinatus in supraspinous fossa using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Rotator cuff muscle tear is one of the most frequent reason of operations in orthopedic surgery. There are several clinical indicators such as Goutallier grade and occupation ratio in the diagnosis and surgery of these disea...

Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.

The Journal of pathology
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated pa...

Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA-PAINT with Machine- Learning-Based Classification.

Small (Weinheim an der Bergstrasse, Germany)
Exosomes are endosome-derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomarkers for cancer diagnostics. However, the present single-variate analysis of exosomes has greatly li...

Machine learning applications in epilepsy.

Epilepsia
Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recognition, lan...

EK-DRD: A Comprehensive Database for Drug Repositioning Inspired by Experimental Knowledge.

Journal of chemical information and modeling
Drug repositioning, or the identification of new indications for approved therapeutic drugs, has gained substantial traction with both academics and pharmaceutical companies because it reduces the cost and duration of the drug development pipeline an...

SleepNet: automated sleep analysis via dense convolutional neural network using physiological time series.

Physiological measurement
OBJECTIVE: In this work, a dense recurrent convolutional neural network (DRCNN) was constructed to detect sleep disorders including arousal, apnea and hypopnea using polysomnography (PSG) measurement channels provided in the 2018 PhysioNet Challenge ...