AIMC Topic: Humans

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Predicting cognitive impairment in chronic kidney disease patients using structural and functional brain network: An application study of artificial intelligence.

Progress in neuro-psychopharmacology & biological psychiatry
OBJECTIVE: To develop and validate artificial intelligence models for the prediction of cognitive impairment in chronic kidney disease (CKD) patients using structural and functional brain network.

Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis.

Journal of neurointerventional surgery
BACKGROUND: Subarachnoid hemorrhage from cerebral aneurysm rupture is a major cause of morbidity and mortality. Early aneurysm identification, aided by automated systems, may improve patient outcomes. Therefore, a systematic review and meta-analysis ...

Deep learning for computational cytology: A survey.

Medical image analysis
Computational cytology is a critical, rapid-developing, yet challenging topic in medical image computing concerned with analyzing digitized cytology images by computer-aided technologies for cancer screening. Recently, an increasing number of deep le...

Quality assurance (QA) for monitoring the performance of assisted reproductive technology (ART) staff using artificial intelligence (AI).

Journal of assisted reproduction and genetics
PURPOSE: Deep learning neural networks have been used to predict the developmental fate and implantation potential of embryos with high accuracy. Such networks have been used as an assistive quality assurance (QA) tool to identify perturbations in th...

Semantic segmentation method for myocardial contrast echocardiogram based on DeepLabV3+ deep learning architecture.

Mathematical biosciences and engineering : MBE
Myocardial contrast echocardiography (MCE) has been proposed as a method to assess myocardial perfusion for the detection of coronary artery diseases in a non-invasive way. As a critical step of automatic MCE perfusion quantification, myocardium segm...

The use of machine learning and artificial intelligence within pediatric critical care.

Pediatric research
The field of pediatric critical care has been hampered in the era of precision medicine by our inability to accurately define and subclassify disease phenotypes. This has been caused by heterogeneity across age groups that further challenges the abil...

Optimization of deep learning models for the prediction of gene mutations using unsupervised clustering.

The journal of pathology. Clinical research
Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital pathology and to predict genetic mutations. Currently, it is commonly assumed that tumor regions have most of the predictive power. However, it is reas...