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 new study shows that retrieval-augmented generation (RAG) can eliminate hallucinations in clinical large language models (LLMs) while protecting patient privacy during contrast media consultations.
More consistent TIL assessments, more accurate patients' prognoses: New research shows how AI sharpens pathologists' interpretation of tissue samples for malignant melanoma.
A new technique called photoacoustic computed tomography (PACT) offers a breast imaging alternative without the discomfort, high costs, or risk associated with the conventional evaluation methods.
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.
An AI-assisted model can take low-quality MRI heart scans and turn them into high quality images, while reducing the time needed to scan the heart by about 90%.
The Pharmaceutical Automation and Digitalisation Congress (AUTOMA+) 2025 welcomes delegates to be a part of its 5th anniversary in Vösendorf, Austria on 24-25 November. This edition focuses on AI-powered pharma, robotics and smart digital solutions.
Digital pathology software company Fujifilm Healthcare Europe and Ibex Medical Analytics, specializing in AI-powered cancer diagnostics, announce a formal partnership to support efficient and accurate cancer diagnosis.
A virtual medical receptionist named “Cassie,” developed through research at Texas A&M University, is designed to transform the way patients interact with health care providers.
Machine learning (ML) for personalised care, large language models for empathy training of cardiologists, wearable sensor data for better screening, and more: Digital technologies hold great potential to improve diagnosis and treatment of patients with atrial fibrillation (AF). At the ESC 2024 cardiology congress in London, four experts explored the benefits of new solutions and pointed out…
If data used to train AI models for medical applications differs from the real-world data, it could lead to patient harm. A new study found proactive strategies to mitigate such data shifts.
Ground-breaking innovation for endovascular surgery: The new software package Endovascular Navigation supports physicians in their interventions with planning, navigation and fusion imaging.
United Imaging, a global leader in cutting-edge diagnostic imaging and radiotherapy solutions, proudly unveils two groundbreaking additions to its portfolio — the uMI Panvivo and the uMR Ultra — both newly CE-marked and set to redefine the standards of precision and performance in medical imaging.
A major challenge in cancer genomics is separating meaningful mutations from false positives. A new tool uses machine learning to significantly reduce these errors.
Cataracts are often treated via SICS surgery in low- and middle-income countries, which often leads to poorer results due to limited resources and training. A new AI-based tool aims to improve this.
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.
Movement disorders often show overlapping symptoms, making it difficult for doctors to make the correct diagnosis. A new AI tool could help distinguish between different disorders, such as tremor and myoclonus.
As Emergency Departments (EDs) get ever busier, focus has fallen on the role artificial Intelligence (AI) can play in supporting patients and clinicians in delivering urgent care. The topic took centre stage in a session looking at the ethics of AI in the ED at the annual congress of the European Society of Emergency Medicine (EUSEM) in Copenhagen.
