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.
By directing radiologists' attention to potentially suspicious areas, AI can help spot more lesions indicative of breast cancer in mammograms. This is suggested by a new study.
At Medical Taiwan 2025, manufacturers attracted attendees with a wide range of innovations. We took a closer look at some of the most exciting companies and their products on display at the medical, health and care expo.
A neural network AI has been trained to detect cardiac amyloidosis from a single echocardiogram video of the heart's apical four-chamber view and differentiate it from similar heart conditions.
Medical Taiwan has long been a showcase for cutting-edge healthcare solutions, but this year marked a pivotal moment. Visitors of the latest edition of the medical, health and care expo in Taipei witnessed a particularly noticeable step forward: the definitive transition of medical AI from promising research to actual clinical practice. Organized by the Taiwan External Trade Development Council…
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.
