
AI picks up mutations in colorectal cancers
A deep learning algorithm picks up molecular pathways and the development of key mutations more accurately than existing methods.
Artificial intelligence has unimaginable potential to revolutionize medicine. We cover the latest technology breakthroughs of machine learning, deep learning algorithms, neural networks and pattern recognition that process mindboggling amounts of data, spot even the smallest detail in medical images and help medical professionals in designing treatment plans.
A deep learning algorithm picks up molecular pathways and the development of key mutations more accurately than existing methods.
AI can detect signals that are informative about mental health from questionnaires and brain scans.
An AI-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy.
Creating human-like AI is about more than mimicking human behaviour – technology must also be able to process information, or ‘think’, if it is to be fully relied upon.
Data privacy and security concerns hamper large-scale studies. Researchers have developed a potential solution.
Secure AI Labs is expanding access to encrypted health care data to advance AI-driven innovation in the field.
AI-based solution FAITH is designed to monitor the mental health status of people who have undergone cancer treatment.
To detect the symptoms that herald the development of psychotic illnesses, scientists have applied longitudinal network analysis to children.
We can run tests and experiments, but we cannot always predict and understand why AI does what it does.
Artificial intelligence has reached a critical turning point in its evolution, according to an international panel of experts.
High-tech 3D facial scans to give us a better understanding of the genetic causes of autism.
Data scientists have used deep learning to identify the right synergistic drug combinations for the rapidly spreading SARS-CoV-2.
Researchers at the University of Bonn show how artificial intelligence improves the evaluation of blood analysis data.
More than 20 hospitals from across the world together with NVIDIA have used AI to predict Covid patients’ oxygen needs on a global scale.
Researchers mimic the animal kingdom’s most basic signs of intelligence in quantum material.
Scientists have developed a novel method that uses artificial intelligence to screen for glaucoma.
Using artificial intelligence, researchers have developed a device for the early detection of autism spectrum disorder in children.
Argonne, industry and academia collaborate to bring innovative AI and simulation tools to the COVID-19 battlefront.
Scientists have developed a bio-compatible implantable AI platform that classifies in real time healthy and pathological patterns in biological signals.
An artificial intelligence blood testing technology was found to detect over 90% of lung cancers in samples from nearly 800 individuals with and without cancer.
Researchers have used machine learning to help reconstruct three-dimensional micro-CT images of fibrous materials.
A deep learning-based technique can be used to eliminate the need for special stains to be prepared by human histotechnologists.
An artificial neural network designed by an international team involving UCL can translate raw data from brain activity, paving the way for new discoveries and a closer integration between technology and the brain.
A team of researchers at Washington University School of Medicine have developed a deep learning model that is capable of classifying a brain tumor as one of six common types using a single 3D MRI scan.
Researchers at the Pennsylvania State University plan to test next-generation artificial intelligence skills withinthe video game Minecraft.
Scientists have developed a machine learning technology to understand how gene expression regulates an organism's circadian clock.
Using a deep learning algorithm, researchers have developed a way to accurately predict which skin cancers are highly metastatic.
A new approach to tackling the spread of malaria in sub-Saharan Africa, which combines affordable, easy-to-administer blood tests with machine learning and unbreakable encryption, has generated encouraging early results in Uganda.
Machine learning can accurately predict cardiovascular disease and guide treatment — but models that incorporate social determinants of health better capture risk and outcomes for diverse groups.