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 in Gastrointestinal Imaging: Advances and Applications.

Radiologic clinics of North America
While artificial intelligence (AI) has shown considerable progress in many areas of medical imaging, applications in abdominal imaging, particularly for the gastrointestinal (GI) system, have notably lagged behind advancements in other body regions. ...

Integrating artificial intelligence with endoscopic ultrasound in the early detection of bilio-pancreatic lesions: Current advances and future prospects.

Best practice & research. Clinical gastroenterology
The integration of Artificial Intelligence (AI) in endoscopic ultrasound (EUS) represents a transformative advancement in the early detection and management of biliopancreatic lesions. This review highlights the current state of AI-enhanced EUS (AI-E...

A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides.

Scientific reports
Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) ...

Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images.

Scientific reports
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate Dementia (M...

IT: An interpretable transformer model for Alzheimer's disease prediction based on PET/MR images.

NeuroImage
Alzheimer's disease (AD) represents a significant challenge due to its progressive neurodegenerative impact, particularly within an aging global demographic. This underscores the critical need for developing sophisticated diagnostic tools for its ear...

Optimized multiple instance learning for brain tumor classification using weakly supervised contrastive learning.

Computers in biology and medicine
Brain tumors have a great impact on patients' quality of life and accurate histopathological classification of brain tumors is crucial for patients' prognosis. Multi-instance learning (MIL) has become the mainstream method for analyzing whole-slide i...

multiPI-TransBTS: A multi-path learning framework for brain tumor image segmentation based on multi-physical information.

Computers in biology and medicine
Brain Tumor Segmentation (BraTS) plays a critical role in clinical diagnosis, treatment planning, and monitoring the progression of brain tumors. However, due to the variability in tumor appearance, size, and intensity across different MRI modalities...

Mitosis detection and classification for breast cancer diagnosis: What we know and what is next.

Computers in biology and medicine
Breast cancer is the second most deadly malignancy in women, behind lung cancer. Despite significant improvements in medical research, breast cancer is still accurately diagnosed with histological analysis. During this procedure, pathologists examine...

Deep learning for cerebral vascular occlusion segmentation: A novel ConvNeXtV2 and GRN-integrated U-Net framework for diffusion-weighted imaging.

Neuroscience
Cerebral vascular occlusion is a serious condition that can lead to stroke and permanent neurological damage due to insufficient oxygen and nutrients reaching brain tissue. Early diagnosis and accurate segmentation are critical for effective treatmen...