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 greater emphasis on AI and sustainability, new approaches to mitigating staff shortage and more: At the European Congress of Radiology (ECR) 2025 in Vienna, Philips showcased its approaches to several critical issues in diagnostic imaging. The global healthtech company presented solutions addressing today's healthcare challenges while aligning with the congress's "Planet…
A rigorous review of evidence showed that AI-assisted technology helps identify colorectal polyps. However, its impact on preventing colon cancer remains unclear.
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.
For Esaote, a leading Italian innovator in medical imaging - ultrasound, dedicated magnetic resonance and medical IT - the mission is to develop new technologies that can help advance diagnosis and improve patient care. Esaote has always leveraged continuous innovation as the key driver of its business strategy. This approach is also embodied in its three business areas.
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.
Machine learning models fail to detect key health deteriorations in the ICU: a new study reveals that 66% of critical injuries in hospitals would go unnoticed if the current AI models were put to use.
Generative AI can detect and quantify cognitive biases of human caregivers during medical emergency situations. This way, LLMs could help reduce the impact of bias based on gender, age, or ethnicity.
A new study reveals that AI can accurately rule out negative low-dose CT (LDCT) scans, potentially reducing the workload of radiologists in lung cancer screening by up to 79%.
A new AI-based approach can predict whether people with type 2 diabetes are likely to develop chronic kidney disease years before symptoms arise, allowing for earlier intervention and treatment.
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.
United Imaging, a global leader in manufacturing advanced medical imaging and radiotherapy equipment, showcases a range of cutting-edge technologies aligned with sustainable values. Notably, the company achieves an A rating in the MSCI ESG ratings, highlighting its unwavering commitment to transforming medical diagnostics and patient care worldwide through a holistic, sustainable approach.
Researchers developed an AI-based system which has has a broad ability to identify even subtle differences between medical images taken at different times, and to predict related outcome measures.
A new AI-enhanced technique makes breast cancer tissue “glow” on MRI scans. This not only improves breast cancer detection but also can help treat it more effectively, the researchers say.
A new open-source automated MRI segmentation tool is setting new standards, developers say. It adapts to any new dataset with minimal user intervention, outperforming similar tools.
A new AI tool creates super-resolution images showing the inner structures of bones in great detail. This can be used to better determine risk for fracture in elderly patients with osteoporosis.
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.
It takes one to know one: Researchers have developed an AI-based evaluation tool to assess how well clinical AI tools perform in the hospital.
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.
New AI-enabled systems, intelligent software, and imaging cloud services for improved radiology workflows: Royal Philips announces its solutions that will be showcased at ECR 2025 in Vienna.
