With the help of artificial intelligence, computers are to simulate human thought processes. Machine learning is intended to support almost all medical specialties. But what is going on inside an AI algorithm, what are its decisions based on? Can you even entrust a medical diagnosis to a machine? Clarifying these questions remains a central aspect of AI research and development.
A novel procedure at UC San Diego Health uses a combination of artificial intelligence and 3D printing to develop a customized implant for the spine during fusion surgery.
An advanced imaging method that uses the natural glow of tissues could help detect subtle differences in the tissue’s biochemistry, offering a way to earlier detect colorectal cancer via endoscopy.
New AI-powered solutions for cardiac ultrasound: Italian medical imaging specialist Esaote will be present at the European Society of Cardiology (ESC) Congress 2025, which starts today (29th August) in Madrid.
Self-learning artificial intelligence approaches are offering a number of advantages for digital pathology when compared to established AI options. The benefits, which range from greater speed and capacitive flexibility to ‘wholly interpretable’ analyses, were outlined at the Digital Pathology and AI Congress in London.
As digital transformation accelerates across healthcare, AIRA Matrix stands at the forefront of artificial intelligence innovation in pathology. The company will showcase its comprehensive portfolio of AI-driven diagnostic and analytical solutions at the upcoming European Congress of Pathology in Vienna this September.
Scientists developed an AI-based approach to diagnose colorectal cancer from different microbial subgroups in the gut microbiota – a non-invasive and low-cost alternative to colonoscopy screening.
Patient communication facilitated by chatbots, image quality optimized by machine learning: Artificial intelligence (AI) is entering radiology at breakneck speed, transforming the specialty almost beyond recognition. So, how will the future of diagnostic imaging under AI look like, and which role will humans still play in it? At the ECR congress in Vienna, experts explored the societal and…
Men assessed as healthy may still have an early form of prostate cancer. Using AI, researchers found signs that were missed in more than 80% of samples of men who later developed cancer.
AI-driven scribes that record patient visits and draft clinical notes for physician review may lead to significant reductions in physician burnout and improvements in well-being, a new study finds.
Henkjan Huisman has been appointed Professor of AI Guided Imaging at Radboud UMC/Radboud University. With a focus on AI applications in medical imaging, his goal is to provide better and more affordable care.
Mammography image interpretation AI models are unreliable – but so are human readers. A new hybrid strategy could reduce radiologist workload by 38% without compromising diagnostic efficacy.
To help people with hearing loss, researchers develop an AI-powered lip-reading camera that translates lip movements into sound. The device could also work in areas with a lot of background noise.
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.
More clinically relevant tumors detected at an earlier stage and at lower costs: New research finds that AI can replace the second radiologist in the Dutch breast cancer screening program.
AI tools for adenoma polyp detection are designed to help increase the accuracy of colonoscopies. However, a new study finds that using AI may lead to loss of detection skills in health professionals.
New research finds that neurosurgery students receiving AI-augmented, personalized feedback from a human instructor have better surgical performance, risk management and skill transfer.
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.
A new AI tool has been shown to accurately predict who would go on to develop leaks in the heart valves – conditions known as regurgitant valvular heart diseases, at a very early stage from an ECG.
By identifying the unique biological signatures that guide AI tissue classification, new research lays the foundation for smart surgical tools with the added feature of biomolecular-level precision.
