Bone scans have been found to overstage prostate cancer at initial staging compared to prostate specific membrane antigen (PSMA) PET, according to new research.
Faster, more accurate and cost-effective testing: Experts outline the beginnings and evolution of “lab-on-a-chip” technology, and its benefits for advanced and next-gen operational platforms.
Voice pathology detection (VPD) can detect abnormal vibrations in the vocal cords caused by conditions like cancer and cysts. Now, researchers have found a way to make the method more reliable.
A team at the University of Bristol has developed a robot manipulator that could carry out clinical breast examinations. The developers hope the device will revolutionise breast health monitoring.
New research from Deusto University in Bilbao, Spain, provides evidence that people can inherit artificial intelligence biases (systematic errors in AI outputs) in their decisions.
A new artificial intelligence (AI) model combines imaging information with clinical patient data to improve diagnostic performance on chest X-rays, a new study finds.
A new survey by The BMJ reveals shortages of vital diagnostic tests for respiratory conditions, such as COPD and asthma, across some of the most deprived areas of England.
Reports of AI gaining the upper hand in diagnostic imaging interpretation are piling up, but there are still areas where the eye of a trained human radiologist remains superior.
Could a single biomarker detect all types of diseases related to dopamine deficiency in the brain? According to a Swedish research group, such a marker may have just been found.
Two out of the four screening tools used by emergency medical services are inadequate for recognising sepsis, according to new research presented at the EUSEM Congress.
A new device that combines microfluidics on paper, electrochemical transduction and immunoassays on magnetic nanoparticles is useful for easy and rapid diagnosis of lung diseases.
Combining ultrasound and MRI technology can help detect prostate cancer at an earlier stage and potentially save lives, according to new University of Dundee research.
Researchers at Monash University have designed a new co-training AI algorithm for medical imaging that can effectively mimic the process of seeking a second opinion.
With the introduction of digital pathology, the University of Queensland and Sullivan Nicolaides Pathology aim to provide significantly improved tests in terms of cost, quality and speed.
Combining two types of heart scan techniques could help doctors to detect deadly hypertrophic cardiomyopathy (HCM) before symptoms and signs on conventional tests appear.
Scientists have developed a tool to create a digital replica of an individual's heart, which could inform the diagnosis and treatment of cardiovascular diseases.
The International Alzheimer's Congress (AAIC) in Amsterdam saw the presentation of new guidelines for diagnosing Alzheimer's disease - with blood biomarkers taking a central role.
A research team at UCLA has made an important advancement to address one of the major challenges in cell-free DNA (cfDNA) testing, also known as liquid biopsy.
New research shows how AI can be used to fuse images from clinical X-ray CT and MRI scans to allow a clearer and more clinically useful interpretation of the images.
A new PET tracer, 89Zr-DFO-girentuximab, can accurately detect a type of kidney cancer called clear cell renal cell carcinoma and differentiate it from other types of kidney tumors.
While it’s true that AI holds tremendous potential for improving the science and practice of psychotherapy, it remains a definitively high-stakes area. Stanford experts define the potential benefits and concerns of deploying the technology.
Researchers at Harvard Medical School developed a new tool that promises to improve the way pathologists see and evaluate a tumor by providing detailed clues about the cancer.
New research suggests that combining blood biomarkers with genomic information more accurately, cost-effectively predicts the risk of developing diseases.
A study led by the National Institutes of Health’s RECOVER Initiative and supported by NYU Langone Health provides an expanded working definition of long Covid.
A University of Arizona Health Sciences-led study found that more than 50% of people don't fully trust AI-powered medical advice, but many put faith in AI if it's monitored and guided by human touch.