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.
Researchers aim to speed up developing drugs against brain diseases through cutting-edge technology. They are generating an innovative technology platform based on high-density microelectrode arrays and 3D networks of human neurons.
Using fluoresence images from live cells, researchers have trained an artificial neural network to reliably recognize cells that are infected by adenoviruses or herpes viruses.
New technology could transform the ability to accurately interpret HIV test results, particularly in low- and middle-income countries.
Researchers used an artificial intelligence (AI) algorithm to sift through terabytes of gene expression data to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu.
With LTech, the Lindera Software Development Kit, health tech company Lindera brings innovation and AI technology to the fitness industry.
Based on 20,000 nights of sleep, researchers have developed an algorithm that can improve the diagnosis, treatment and overall understanding of sleep disorders.
Researchers discovered that AI models have a tendency to look for shortcuts. In the case of AI-assisted disease detection, these shortcuts could lead to diagnostic errors if deployed in clinical settings.
The University of Texas at San Antonio (UTSA) has established a wearables and artificial intelligence laboratory to provide precision treatment plans to improve learning among those diagnosed with autism spectrum disorder (ASD).
A team of engineers from Rensselaer Polytechnic Institute and clinicians from Massachusetts General Hospital developed a deep learning algorithm that can help assess a patient's risk of cardiovascular disease with the same low-dose computerized tomography (CT) scan used to screen for lung cancer.
A new study from the Mayo Clinic found that differences between a person's age in years and his or her biological age, as predicted by an artificial intelligence (AI)-enabled EKG, can provide measurable insights into health and longevity.
An artificial intelligence (AI) program accurately predicts the risk that lung nodules detected on screening CT will become cancerous, according to a new study.
The overfitted brain: Our dreams' weirdness might be why we have them, argues a researchers in new theory of dreaming.
Researchers have developed a new "multi-modal" image fusion method based on supervised deep learning that enhances image clarity, reduces redundant image features and supports batch processing.
AI-driven healthcare has the potential to transform medical decision-making and treatment, but these algorithms must be thoroughly tested and continuously monitored to avoid unintended consequences to patients.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days.
Neural network framework may increase radiologist's confidence in assessing the type of lung cancer on CT scans, informing individualized treatment planning.
Machine learning helps some of the best microscopes to see better, work faster, and process more data.
Researchers propose a deep learning-based model for mimicking and continuously modifying speaker voice identity during speech translation.
Researchers use AI software to predict coronary artery plaque composition and significance without the risks of invasive procedures.
A study from Stanford University found limitations in the Food and Drug Administration’s approval process.
A neural network that mimics the biology of the brain can be loaded onto a microchip for faster and more efficient artificial intelligence.
Artificial intelligence could help to optimise the development of antibody drugs. This leads to active substances with improved properties, also with regard to tolerability in the body.
Researchers have investigated how machine learning can be used to find effective testing methods during epidemic outbreaks, thereby helping to better control the outbreaks.
Human-machine interaction is complex. Researchers investigate a new form of interaction between humans and machines.
Powerful algorithms used by Netflix, Amazon and Facebook can ‘predict’ the biological language of cancer and neurodegenerative diseases like Alzheimer's.
Researchers combined motion analysis that uses smartphone application and machine learning that uses an anomaly detection method, thereby developing a technique to easily screen for carpal tunnel syndrome.
Researchers have created a machine learning model that helps identify bipolar disorder at earlier stages.
Artificial Intelligence is now capable of generating novel, functionally active proteins.
Researchers have developed an AI platform that could one day be used in a system to assess vascular and eye diseases.
