AIMC Topic: Neural Networks, Computer

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Exploring the performance of implicit neural representations for brain image registration.

Scientific reports
Pairwise image registration is a necessary prerequisite for brain image comparison and data integration in neuroscience and radiology. In this work, we explore the efficacy of implicit neural representations (INRs) in improving the performance of bra...

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.

Scientific reports
We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comp...

Cow detection and tracking system utilizing multi-feature tracking algorithm.

Scientific reports
In modern cattle farm management systems, video-based monitoring has become important in analyzing the high-level behavior of cattle for monitoring their health and predicting calving for providing timely assistance. Conventionally, sensors have been...

Epigenetic target identification strategy based on multi-feature learning.

Journal of biomolecular structure & dynamics
The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics incr...

Classification of patients with chronic disease by activation level using machine learning methods.

Health care management science
Patient Activation Measure (PAM) measures the activation level of patients with chronic conditions and correlates well with patient adherence behavior, health outcomes, and healthcare costs. PAM is increasingly used in practice to identify patients n...

View-independent gait events detection using CNN-transformer hybrid network.

Journal of biomedical informatics
Accurate gait detection is crucial in utilizing the ample health information embedded in it. Vision-based approaches for gait detection have emerged as an alternative to the exacting sensor-based approaches, but their application has been rather limi...

Unsupervised deep learning registration model for multimodal brain images.

Journal of applied clinical medical physics
Multimodal image registration is a key for many clinical image-guided interventions. However, it is a challenging task because of complicated and unknown relationships between different modalities. Currently, deep supervised learning is the state-of-...

Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning.

Molecules (Basel, Switzerland)
Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network re...

U-Net based vessel segmentation for murine brains with small micro-magnetic resonance imaging reference datasets.

PloS one
Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets....

Artificial intelligence quantifying endoscopic severity of ulcerative colitis in gradation scale.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: Existing endoscopic scores for ulcerative colitis (UC) objectively categorize disease severity based on the presence or absence of endoscopic findings; therefore, it may not reflect the range of clinical severity within each category. How...