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AI keeps an eye on health AI
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.
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.
Researchers developed a smart patch capable of real-time biometric signal monitoring and drug delivery. Potential applications include glucose management, pain relief, and chronic disease treatment.
A sensor, similar to glucose monitoring devices, detects lung cancer biomarkers from a blood sample in just 40 minutes. The technology has potential to identify at-risk patients and tailor treatments.
“A turning point in neuroscience,” say developers about a holographic endoscope that peers deep into the brain through an optical fiber – minimally invasive and with subcellular resolution.
Patient-specific 3D printed surgical guides could provide a clear visual aid that helps cardiac surgeons locate key treatment areas on the heart, such as the optimal location to build the bypass vein.
Less than a millimetre: the world's smallest biomedical robot is designed for imaging, sampling, drug delivery, and laser ablation. The developers highlight potential new clinical applications.
A survey found that many Americans use a device to monitor their heart, but few share that data with their doctor. Cardiologists explain when findings should be discussed with a medical professional.
Promising technology for patients with spinal cord injuries: A new study paves the way for complex touch sensation through brain stimulation, using an extracorporeal bionic limb.
Anyone who has exchanged a few lines of dialogue with a large language model (LLM), will probably agree that generative AI is an impressive new breed of technology. LLMs show great potential in addressing some of the most urgent challenges in healthcare. At the Medica tradefair, several expert sessions were dedicated to generative AI, its potential medical applications and current caveats.
New insights on the degradation of implantable chips in the body could lead to enhanced longevity of the chips and better treatments for patients with Parkinson's or clinical depression.
Researchers have developed an AI-based model to better predict whether cancer patients will benefit from immunotherapy — using only routine blood tests and clinical data.
Can an AI determine whether or not a person drinks beer by looking at their knee X-rays? It can't – but the claim shows why “shortcut learning” is such a dangerous mechanism in medical AI.
US engineers turned to the world of parasites as inspiration to affix small-scale medical devices to the GI tract or other soft tissues for sensing, sample collection, and extended drug release.
Large language models (LLM) show promise in detecting hospital patients at risk of committing suicide. This could help warn medical staff in time while maintaining the patients' privacy.
Opposing views on new implantable cardiac devices were aired in a Great Debate session at the European Society of Cardiology’s annual 2024 congress in London. Experts discussed emerging techniques and technologies and debated whether they are actually ready for clinical application. At the core of the session was the issue of whether conduction system pacing (CSP) should replace cardiac…
Precise segmentation of anatomical structures greatly benefits cancer diagnosis. Using AI and deep learning methods, researchers are developing a high-precision 3D viewer software for medical image data.
To advance the transition of AI from research to clinical application, Nvidia announced that Siemens Healthineers has adopted MONAI, an open-source medical imaging framework.
Detection of patient falls, unauthorized intrusions on hospital premises, and more: A new suite of AI tools is designed to enhance healthcare security and patient safety surveillance.
In the world of theatre, the ‘deus ex machina’, the god from the machine, is a dramaturgical trick to resolve seemingly unsolvable conflicts. Can artificial intelligence (AI) also be such a universal problem solver for internal medicine? At the Annual Congress of the German Society of Internal Medicine (DGIM), Dr Isabella Wiest explored the potential – and limitations – of AI helpers.
Monitoring brainwaves and diagnosing neurological conditions could benefit from a novel 3D printing technology, which applies liquid ink onto a patient’s scalp to measure brain activity.
US researchers have developed a comprehensive deep learning AI model designed to more accurately identify and classify cells in high-content tissue images.
Large language models (LLMs) have potential in healthcare settings to help support both patients and clinicians. Cardiologist Dr Robert van der Boon believes they could have several applications, including patient communication and education, clinical decision support and administrative tasks. Delegates to ESC 2024 in London heard roles explored for LLMs in areas of clinical decision-making,…
Future-oriented large-scale investments on the one hand, political unrest on the other: The presentation of award-winning medical technology from Taiwan at Medica in Düsseldorf reflected a year full of changes and challenges. The prize-winning solutions for surgery, intensive care medicine, traumatology and endoscopy once again attracted a large professional audience.
A new study investigating the impact of AI in healthcare shows that using LLMs to process thousands of patient records daily across multiple hospitals could lead to substantial resource consumption.
The journey of a baby through the birth canal can be fraught with obstacles and risks. A new AI-based tool to evaluate the head position of the baby could lead to fewer childbirth complications.