AIMC Topic: Algorithms

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JotlasNet: Joint tensor low-rank and attention-based sparse unrolling network for accelerating dynamic MRI.

Magnetic resonance imaging
Joint low-rank and sparse unrolling networks have shown superior performance in dynamic MRI reconstruction. However, existing works mainly utilized matrix low-rank priors, neglecting the tensor characteristics of dynamic MRI images, and only a global...

Self-supervised 3D medical image segmentation by flow-guided mask propagation learning.

Medical image analysis
Despite significant progress in 3D medical image segmentation using deep learning, manual annotation remains a labor-intensive bottleneck. Self-supervised mask propagation (SMP) methods have emerged to alleviate this challenge, allowing intra-volume ...

Adjacent point aided vertebral landmark detection and Cobb angle measurement for automated AIS diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Adolescent Idiopathic Scoliosis (AIS) is a prevalent structural deformity disease of human spine, and accurate assessment of spinal anatomical parameters is essential for clinical diagnosis and treatment planning. In recent years, significant progres...

Multimodal Cross Global Learnable Attention Network for MR images denoising with arbitrary modal missing.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Magnetic Resonance Imaging (MRI) generates medical images of multiple sequences, i.e., multimodal, from different contrasts. However, noise will reduce the quality of MR images, and then affect the doctor's diagnosis of diseases. Existing filtering m...

A deep learning model for QRS delineation in organized rhythms during in-hospital cardiac arrest.

International journal of medical informatics
BACKGROUND: Cardiac arrest (CA) is the sudden cessation of heart function, typically resulting in loss of consciousness and cessation of pulse and breathing. The electrocardiogram (ECG) stands as an essential tool extensively utilized by clinicians, ...

ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.)
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...

The use of artificial intelligence to aid the diagnosis of lung cancer - A retrospective-cohort study.

Radiography (London, England : 1995)
INTRODUCTION: AI software in the form of deep learning-based automatic detection (DLAD) algorithms for chest X-ray (CXR) interpretation have shown success in early detection of lung cancer (LC), however, there remains uncertainty related to clinical ...

Construction and evaluation of machine learning-based predictive models for early-onset preeclampsia.

Pregnancy hypertension
OBJECTIVE: To analyze the influencing factors of early-onset preeclampsia (EOPE). And to construct and validate the prediction model of EOPE using machine learning algorithm.

Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model.

BMC bioinformatics
BACKGROUND: Biomedical text mining is a technique that extracts essential information from scientific articles using named entity recognition (NER). Traditional NER methods rely on dictionaries, rules, or curated corpora, which may not always be acce...

Optimized convolutional neural network using African vulture optimization algorithm for the detection of exons.

Scientific reports
The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still re...