The slow adoption of blockchain technology is partly driven by overhyped promises that often obscure the complex technological, organisational, and environmental challenges, according to research from the University of Surrey.

Blockchain is a secure digital ledger that records and verifies transactions across many computers in a way that's hard to alter.

A joint research team from the University of Canberra and Kuwait College of Science and Technology has achieved groundbreaking detection of Parkinson's disease with near-perfect accuracy, simply by analyzing brain responses to emotional situations like watching video clips or images. The findings offer an objective way to diagnose the debilitating movement disorder, instead of relying on clinical expertise and patient self-assessments, potentially enhancing treatment options and overall well-being for those affected by Parkinson's disease.

Using just one inhalation lung CT scan, a deep learning model can accurately diagnose and stage chronic obstructive pulmonary disease (COPD), according to a study published today in Radiology: Cardiothoracic Imaging, a journal of the Radiological Society of North America (RSNA).

COPD is a group of progressive lung diseases that impair a person's ability to breathe.

Researchers from Imperial College London, working with the company MakeSense Technology and the charity Bravo Victor, have developed a shape-changing device called Shape that helps people with visual impairment navigate through haptic perception - the way people understand information about objects through touch. The device, which looks like a torch, bends to indicate where a person needs to move and straightens when the user is facing the correct direction.

Scientists from Universidad Carlos III de Madrid (UC3M), together with a research team from Ericsson and the KTH Royal Institute of Technology in Sweden, have developed an artificial intelligence-based software programme that can search for information and make recommendations for biomedical image analysis. This innovation streamlines the work of individuals using large bioimage databases, including life sciences researchers, workflow developers, and biotech and pharmaceutical companies.

A new study from Washington University School of Medicine in St. Louis describes an innovative method of analyzing mammograms that significantly improves the accuracy of predicting the risk of breast cancer development over the following five years. Using up to three years of previous mammograms, the new method identified individuals at high risk of developing breast cancer 2.3 times more accurately than the standard method, which is based on questionnaires assessing clinical risk factors alone, such as age, race and family history of breast cancer.

Brian Hie runs the Laboratory of Evolutionary Design at Stanford, where he works at the crossroads of artificial intelligence and biology. Not long ago, Hie pondered a provocative question: If a tool like ChatGPT can write original sentences based on patterns found in massive collections of previously written words, what happens if we replace written words with genetic code?