AIMC Topic: Humans

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Deciphering epigenomic code for cell differentiation using deep learning.

BMC genomics
BACKGROUND: Although DNA sequence plays a crucial role in establishing the unique epigenome of a cell type, little is known about the sequence determinants that lead to the unique epigenomes of different cell types produced during cell differentiatio...

EUSKOR: End-to-end coreference resolution system for Basque.

PloS one
This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristics of the language. The module has been integrated in a linguistic analysis pipeline obtaining an end...

Decoding Brain States From fMRI Signals by Using Unsupervised Domain Adaptation.

IEEE journal of biomedical and health informatics
With the development of deep learning in medical image analysis, decoding brain states from functional magnetic resonance imaging (fMRI) signals has made significant progress. Previous studies often utilized deep neural networks to automatically clas...

CIGuide: in situ augmented reality laser guidance.

International journal of computer assisted radiology and surgery
PURPOSEĀ : A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal ment...

Artificial Intelligence in Radiation Oncology.

Hematology/oncology clinics of North America
The integration of artificial intelligence in the radiation oncologist's workflow has multiple applications and significant potential. From the initial patient encounter, artificial intelligence may aid in pretreatment disease outcome and toxicity pr...

Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration.

Medical image analysis
Convolutional neural networks (CNNs) have recently led to significant advances in automatic segmentations of anatomical structures in medical images, and a wide variety of network architectures are now available to the research community. For applica...

Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

Experimental gerontology
INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, a...

Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram (EEG) signals of patients with epilepsy, their conditions can be monito...