Gadolinium-based contrast agents enhance visibility but also pose a significant health risk. A new AI-powered virtual MRI imaging technique is designed to offer a safer diagnostic approach.
Microsatellite instability-high (MSI-H) tumors are associated with better clinical outcomes. A novel AI model for accurate MSI prediction could help battle gastric and colorectal cancers.
Analyzing heart imaging and a full spectrum of medical records, a new AI tool can reveal previously hidden information about a patient’s heart health, including predictions of sudden cardiac arrest.
A research group at Osaka Metropolitan University developed an AI model that can detect the presence of hepatic steatosis (fatty liver disease) from chest X-ray images.
Survival rates for pancreatic cancer rise drastically the earlier it is detected, but early-stage tumors are notoriously difficult to spot. A new AI-powered diagnostic system is set to improve this.
A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT (LDCT) scan, according to new research published at the ATS 2025 International Conference.
A novel deep-learning approach automatically finds and classifies microcalcifications found in mammography images—bringing both accuracy and consistency to breast-cancer screening.
Results of a new retrospective study demonstrate the potential of a novel, CT-based deep learning-driven tool to enhance liver cancer diagnosis, treatment planning, and response evaluation.
Researchers have developed an AI tool that creates synthetic yet medically accurate models of fibrotic heart tissue (heart scarring), aiding treatment planning for atrial fibrillation (AF) patients.
Despite previous global declines, pulmonary tuberculosis (TB) is on the rise again. A new AI-powered lung ultrasound shows promise in improving diagnostic performance of TB.
A new AI tool can extract key information from brain MRI scans of multiple sclerosis (MS) patients. This could be used to improve disease and treatment response monitoring.
New findings show how AI-assisted mammography may not only reveal breast cancer, but can also assess calcium buildup in the arteries within breast tissue—an indicator of cardiovascular health.
To reduce the radiation exposure for patients undergoing frequent CT scans for pneumonia diagnosis, deep learning-based denoising of ultra-low dose CT presents a viable alternative.
Researchers developed an advanced AI tool for automatic analysis of colorectal cancer tissue slides. The new model outperformed all predecessors in the classification of tissue microscopy samples.
Analysing long-term ECG recordings for signs of heart abnormalities such as arrhythmias is a time-consuming process. New research finds that AI is better suited for this task than humans.
Using 3D imaging and deep learning AI, researchers have developed a new way to accurately assess body fat and muscle distribution, which are crucial for understanding health risks.
A new deep learning model shows promise in detecting and segmenting lung tumors. The findings of the study could have important implications for lung cancer treatment.
Precise segmentation of anatomical structures greatly benefits cancer diagnosis. Using AI and deep learning methods, researchers are developing a high-precision 3D viewer software for medical image data.
US researchers have developed a comprehensive deep learning AI model designed to more accurately identify and classify cells in high-content tissue images.
