AIMC Topic: Algorithms

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Adaptive debiasing learning for drug repositioning.

Journal of biomedical informatics
Drug repositioning, pivotal in current pharmaceutical development, aims to find new uses for existing drugs, offering an efficient and cost-effective path to drug discovery. In recent years, graph neural network-based deep learning methods have achie...

The implementation of artificial intelligence in serial monitoring of post gamma knife vestibular schwannomas: A pilot study.

Clinical imaging
BACKGROUND: Vestibular schwannomas (VS) are benign tumors that can lead to hearing loss, balance issues, and tinnitus. Gamma Knife Radiosurgery (GKS) is a common treatment for VS, aimed at halting tumor growth and preserving neurological function. Ac...

AttriMIL: Revisiting attention-based multiple instance learning for whole-slide pathological image classification from a perspective of instance attributes.

Medical image analysis
Multiple instance learning (MIL) is a powerful approach for whole-slide pathological image (WSI) analysis, particularly suited for processing gigapixel-resolution images with slide-level labels. Recent attention-based MIL architectures have significa...

Fast cortical thickness estimation using deep learning-based anatomy segmentation and diffeomorphic registration.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurately and efficiently estimating the cortical thickness from magnetic resonance images (MRIs) is crucial for neuroscientific studies and clinical applications with various large-scale datasets. Diffeomorphic registration-based cortical thickness...

CALIMAR-GAN: An unpaired mask-guided attention network for metal artifact reduction in CT scans.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
High-quality computed tomography (CT) scans are essential for accurate diagnostic and therapeutic decisions, but the presence of metal objects within the body can produce distortions that lower image quality. Deep learning (DL) approaches using image...

REPAIR: Reciprocal assistance imputation-representation learning for glioma diagnosis with incomplete MRI sequences.

Medical image analysis
The absence of MRI sequences is a common occurrence in clinical practice, posing a significant challenge for prediction modeling of non-invasive diagnosis of glioma (GM) via fusion of multi-sequence MRI. To address this issue, we propose a novel unif...

Machine Learning-Based Prediction to Support ICU Admission Decision Making among Very Old Patients with Respiratory Infections: A Proof of Concept on a Nationwide Population-Based Cohort Study.

Medical decision making : an international journal of the Society for Medical Decision Making
BackgroundIntensive care unit (ICU) hospitalizations of very old patients with acute respiratory infection have risen. The decision-making process for ICU admission is multifaceted, and the prediction of long-term survival outcome is an important com...

SegQC: a segmentation network-based framework for multi-metric segmentation quality control and segmentation error detection in volumetric medical images.

Medical image analysis
Quality control (QC) of structures segmentation in volumetric medical images is important for identifying segmentation errors in clinical practice and for facilitating model development by enhancing network performance in semi-supervised and active l...

AdaptFRCNet: Semi-supervised adaptation of pre-trained model with frequency and region consistency for medical image segmentation.

Medical image analysis
Recently, large pre-trained models (LPM) have achieved great success, which provides rich feature representation for downstream tasks. Pre-training and then fine-tuning is an effective way to utilize LPM. However, the application of LPM in the medica...

Bi-VesTreeFormer: A bidirectional topology-aware transformer framework for coronary vFFR estimation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Fractional Flow Reserve (FFR) serves as the gold standard for evaluating the functional significance of coronary artery stenosis. However, traditional FFR involves the injection of vasodilator drugs and the utilization of additional guidewires, which...