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.
Researchers have created a system that uses generative AI to study the shape and structure of blood cells, and spot unusual or rare cells that may indicate disease such as leukaemia.
Philips and Cortechs.ai have extended their collaboration to integrate AI-enabled quantitative neuroimaging analytics directly into MR systems. The partnership aims to provide radiologists with automated, objective measurements of brain structures and lesions to support diagnosis and monitoring of neurological conditions.
Artificial intelligence (AI) is transforming healthcare, but it also introduces new cybersecurity risks that challenge IT teams. While AI streamlines diagnosis and workflow, cybercriminals are leveraging the same technology to infiltrate hospital systems. Experts addressed these emerging threats and strategies for resilience during the ‘Maximising What You Have for Cyber Resilience – Ask the…
Today, language barriers in healthcare can be easily overcome – leading to improved patient care. Pocketalk, the global leader in translation hardware, software, and integration, delivers accurate, mobile, and secure translations that exceed industry security standards.
A new study shows how AI could transform medical education, while calling for stronger collaboration across schools, hospitals, and regulators to make it safe, responsible, and effective.
People facing a mental health crisis increasingly turn to AI chatbots and wellness apps for emotional support. However, these tools alone do not have what it takes, according to a new health advisory.
In a CT scan of the lungs, accidentally inhaled objects can be extremely subtle and easy to miss, even for experienced clinicians. A new AI model acts as a “second set of eyes” to help detect hidden cases.
Europe’s healthcare systems face growing pressure: fewer staff, higher infection-control demands, and increased documentation. Estonia is already built for this. With 99% of health data digital, digital trust is built into everyday healthcare – giving Estonian companies a strong foundation for efficient collaboration, fast traceability, and AI-supported operations.
Researchers developed an AI-assisted brain atlas for visualization at microscopic detail using MRI scans. The tool could transform early detection of Alzheimer's and other neurological diseases.
A biosensor that identifies volatile organic compounds (VOCs) in exhaled breath could be used in conjunction with AI to detect various thoracic cancers including lung cancer.
In emergency settings, AI to analyze ECG data can improve detection of severe heart attacks, including those with unconventional symptoms, or atypical ECG patterns, and reduced false positives.
Developmental dysplasia of the hip occurs in 2-4% of infants, but screening via ultrasound is notoriously hard to master. An AI-assisted application could prevent many unnecessary hospital referrals.
At the 38th European Association of Nuclear Medicine (EANM) Congress, held from October 4–8 in Barcelona, United Imaging, a global manufacturer of cutting-edge medical imaging technology, showcases its most advanced AI-powered molecular imaging innovations, the uMI Panvivo family and the uMI Panorama family, and highlights the company’s strong growth and confidence in the European market.
An international team has developed an AI model that brings together medical imaging data and clinical information to calculate the risk of breast cancer tumour recurrence more accurately.
Underscoring the growing role of large language models (LLM) in cancer care, ESMO released the first structured set of recommendations to bring AI language models into oncology safely and effectively.
An AI system that can predict what a patient’s knee X-ray will look like a year in the future could transform how millions of people with osteoarthritis understand and manage their condition.
Overcrowded EDs and the escalating workload of nurses are pressing challenges in emergency medicine. While AI might not solve these problems, it could help staff mitigate them, new research suggests.
Healthcare stands at a crossroads. With an impending shortage of 11 million healthcare workers by 2030 and millions dying annually from poor-quality care, the industry desperately needs transformation. Dr. Alex Ng from Tencent Healthcare explores how artificial intelligence is emerging as a powerful catalyst—not to replace human expertise, but to amplify it.
This year, the Journées Francophones de Radiologie (JFR) will carry a clinical ambition as simple as it is essential: to shine a spotlight on those who are often overlooked. Under the presidency of Professor Mathieu Lederlin, thoracic radiologist at Rennes University Hospital, vulnerable patients will be at the heart of the annual meeting of the French Society of Radiology that will unfold…
