AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Imaging, Three-Dimensional

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Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study.

Orthopaedic surgery
BACKGROUND: The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicator...

Machine Learning Approaches for 3D Motion Synthesis and Musculoskeletal Dynamics Estimation: A Survey.

IEEE transactions on visualization and computer graphics
The inference of 3D motion and dynamics of the human musculoskeletal system has traditionally been solved using physics-based methods that exploit physical parameters to provide realistic simulations. Yet, such methods suffer from computational compl...

Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning.

Parasites & vectors
BACKGROUND: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understanding of their behaviour to devise effective disease control strategies. In this article we show that machine learning can provide a performance assessme...

Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.

IEEE transactions on medical imaging
Fairness (also known as equity interchangeably) in machine learning is important for societal well-being, but limited public datasets hinder its progress. Currently, no dedicated public medical datasets with imaging data for fairness learning are ava...

Shape-Scale Co-Awareness Network for 3D Brain Tumor Segmentation.

IEEE transactions on medical imaging
The accurate segmentation of brain tumor is significant in clinical practice. Convolutional Neural Network (CNN)-based methods have made great progress in brain tumor segmentation due to powerful local modeling ability. However, brain tumors are freq...

Morphometric analysis and tortuosity typing of the large intestine segments on computed tomography colonography with artificial intelligence.

Colombia medica (Cali, Colombia)
BACKGROUND: Morphological properties such as length and tortuosity of the large intestine segments play important roles, especially in interventional procedures like colonoscopy.

Gender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and Artificial Neural Networks.

Nigerian journal of clinical practice
BACKGROUND: Sex determination from the bones is of great importance for forensic medicine and anthropology. The mandible is highly valued because it is the strongest, largest and most dimorphic bone in the skull.

Artificial intelligence and mixed reality for dental implant planning: A technical note.

Clinical implant dentistry and related research
AIM: The aim of this work is to present a new protocol for implant surgical planning which involves the combined use of artificial intelligence (AI) and mixed reality (MR).

Enhanced choroid plexus segmentation with 3D UX-Net and its association with disease progression in multiple sclerosis.

Multiple sclerosis and related disorders
BACKGROUND: The choroid plexus (CP) is suggested to be closely associated with the neuroinflammation of multiple sclerosis (MS). Segmentation based on deep learning (DL) could facilitate rapid and reproducible volume assessment of the CP, which is cr...

Medical image registration via neural fields.

Medical image analysis
Image registration is an essential step in many medical image analysis tasks. Traditional methods for image registration are primarily optimization-driven, finding the optimal deformations that maximize the similarity between two images. Recent learn...