AI Medical Compendium Topic

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

Image Interpretation, Computer-Assisted

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Artificial intelligence for retinal diseases.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To discuss the worldwide applications and potential impact of artificial intelligence (AI) for the diagnosis, management and analysis of treatment outcomes of common retinal diseases.

Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding.

Scientific reports
This study aims to explore the efficacy of a hybrid deep learning and radiomics approach, supplemented with patient metadata, in the noninvasive dermoscopic imaging-based diagnosis of skin lesions. We analyzed dermoscopic images from the Internationa...

Computerizing the first step of the two-step algorithm in dermoscopy: A convolutional neural network for differentiating melanocytic from non-melanocytic skin lesions.

European journal of cancer (Oxford, England : 1990)
IMPORTANCE: Convolutional neural networks (CNN) have shown performance equal to trained dermatologists in differentiating benign from malignant skin lesions. To improve clinicians' management decisions, additional classifications into diagnostic cate...

Accuracy of vestibular schwannoma segmentation using deep learning models - a systematic review & meta-analysis.

Neuroradiology
UNLABELLED: Vestibular Schwannoma (VS) is a rare tumor with varied incidence rates, predominantly affecting the 60-69 age group. In the era of artificial intelligence (AI), deep learning (DL) algorithms show promise in automating diagnosis. However, ...

Artificial intelligence-assisted volume isotropic simultaneous interleaved bright- and black-blood examination for brain metastases.

Neuroradiology
PURPOSE: To verify the effectiveness of artificial intelligence-assisted volume isotropic simultaneous interleaved bright-/black-blood examination (AI-VISIBLE) for detecting brain metastases.

Skeleton-guided multi-scale dual-coordinate attention aggregation network for retinal blood vessel segmentation.

Computers in biology and medicine
Deep learning plays a pivotal role in retinal blood vessel segmentation for medical diagnosis. Despite their significant efficacy, these techniques face two major challenges. Firstly, they often neglect the severe class imbalance in fundus images, wh...

Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain.

Investigative radiology
Recent technological advancements have revolutionized routine brain magnetic resonance imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease evaluation. This review explores 2 pivotal breakthrough areas: deep lear...

An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images.

Sensors (Basel, Switzerland)
Stroke is the second leading cause of death and a major cause of disability around the world, and the development of atherosclerotic plaques in the carotid arteries is generally considered the leading cause of severe cerebrovascular events. In recent...

MASDF-Net: A Multi-Attention Codec Network with Selective and Dynamic Fusion for Skin Lesion Segmentation.

Sensors (Basel, Switzerland)
Automated segmentation algorithms for dermoscopic images serve as effective tools that assist dermatologists in clinical diagnosis. While existing deep learning-based skin lesion segmentation algorithms have achieved certain success, challenges remai...