Computers and Math from Science Daily Feed

Researchers have developed a method to use an image generation AI model to create realistic images of single cells, which are then used as 'synthetic data' to train an AI model to better carry out single-cell segmentation.

A sensing technology that can assess the quality of components in fields such as aerospace could transform UK industry.

Physicists have shown that ultra-thin two-dimensional materials such as tungsten diselenide can rotate the polarization of visible light by several degrees at certain wavelengths under small magnetic fields suitable for use on chips.

Atrial fibrillation is the most common cardiac arrhythmia worldwide with around 59 million people concerned in 2019. This irregular heartbeat is associated with increased risks of heart failure, dementia and stroke. It constitutes a significant burden to healthcare systems, making its early detection and treatment a major goal. Researchers have recently developed a deep-learning model capable of predicting the transition from a normal cardiac rhythm to atrial fibrillation. It gives early warnings on average 30 minutes before onset, with an accuracy of around 80%. These results pave the way for integration into wearable technologies, allowing early interventions and better patient outcomes.

The study highlights the rapid progress and transformative potential of AI in weather prediction.

Magnetic two-dimensional materials consisting of one or a few atomic layers have only recently become known and promise interesting applications, for example for the electronics of the future. So far, however, it has not been possible to control the magnetic states of these materials well enough. A research team is now presenting an innovative idea that could overcome this shortcoming -- by allowing the 2D layer to react with hydrogen.

State-of-the-art artificial intelligence systems known as large language models (LLMs) are poor medical coders, according to researchers. Their study emphasizes the necessity for refinement and validation of these technologies before considering clinical implementation. The study extracted a list of more than 27,000 unique diagnosis and procedure codes from 12 months of routine care in the Mount Sinai Health System, while excluding identifiable patient data. Using the description for each code, the researchers prompted models from OpenAI, Google, and Meta to output the most accurate medical codes. The generated codes were compared with the original codes and errors were analyzed for any patterns.

An international collaboration of researchers has achieved a significant breakthrough in quantum technology, with the successful demonstration of quantum interference among several single photons using a novel resource-efficient platform. The work represents a notable advancement in optical quantum computing that paves the way for more scalable quantum technologies.

Researchers have unveiled a new means of predicting how to synthesize new materials via the ion-exchange. Based on computer simulations, the method significantly reduces the time and energy required to explore for inorganic materials.

A new robotic suction cup which can grasp rough, curved and heavy stone, has been developed by scientists.

A new typing model simulates the typing process instead of just predicting words.

Contrary to previous assumptions, nerve cells in the human neocortex are wired differently than in mice. The study found that human neurons communicate in one direction, while in mice, signals tend to flow in loops. This increases the efficiency and capacity of the human brain to process information. These discoveries could further the development of artificial neural networks.

Scientists have discovered that the magnetic nanobubbles known as skyrmions can be moved by electrical currents, attaining record speeds up to 900 m/s. Anticipated as future bits in computer memory, these nanobubbles offer enhanced avenues for information processing in electronic devices. Their tiny size provides great computing and information storage capacity, as well as low energy consumption. Until now, these nanobubbles moved no faster than 100 m/s, which is too slow for computing applications. However, thanks to the use of an antiferromagnetic material as medium, the scientists successfully had the skyrmions move 10 times faster than previously observed. These results offer new prospects for developing higher-performance and less energy-intensive computing devices.

Most cancer patients do not benefit from early targeted therapies. Scientists now describe a new computational pipeline to systematically predict patient response to cancer drugs at single-cell resolution.

Monitoring and treating a case of multiple sclerosis requires reliable and long-term data on how the disease is progressing in the person in question. Fitness trackers and smartphones can supply this data, as a research team has now shown.

Researchers are targeting the next generation of soft actuators and robots with an elastomer-based ink for 3D printing objects with locally changing mechanical properties, eliminating the need for cumbersome mechanical joints.

AI developments in chemical biology could unlock new types of disease treatments.

Soft skin coverings and touch sensors have emerged as a promising feature for robots that are both safer and more intuitive for human interaction, but they are expensive and difficult to make. A recent study demonstrates that soft skin pads doubling as sensors made from thermoplastic urethane can be efficiently manufactured using 3D printers.

A study has found that the AI model GPT-4 significantly exceeds the ability of non-specialist doctors to assess eye problems and provide advice.

Researchers have used artificial intelligence techniques to massively accelerate the search for Parkinson's disease treatments. The researchers designed and used an AI-based strategy to identify compounds that block the clumping, or aggregation, of alpha-synuclein, the protein that characterises Parkinson's.