Many consider our eyes to be the windows to the soul. Yet the cornea, the panes of these windows, sometimes need significant repair. Friso Heslinga, PhD, created artificial intelligence models to support surgeons in one of the oldest and most common transplantation procedures.
A new system capable of reading lips with remarkable accuracy even when speakers are wearing face masks could help create a new generation of hearing aids.
New CT technology paired with artificial intelligence-based noise reduction offers superior detection of bone disease associated with multiple myeloma at lower radiation doses than conventional CT.
UK researchers developed and validated a deep learning algorithm that can identify and outline a non-small cell lung cancer (NSCLC) tumor on a CT scan within seconds.
The combination of deep-learning reconstruction and a subtraction technique yields promising diagnostic performance for the detection of in-stent restenosis by coronary CTA.
Using deep learning, researchers created AI-driven computer models to analyze corneal and retinal images to help eye doctors in the future.
A new AI platform can analyze genomic data extremely quickly, picking out key patterns to classify different types of colorectal tumors and improve the drug discovery process.
An algorithm built to assess scar patterns in patient heart tissue can predict potentially life-threatening arrhythmias more accurately than doctors can.
Big data is transforming diagnosis and medical care, but the critical challenge remains over how to equally apply the benefits it delivers across real-world clinical settings, according to industry expert Prof Benoît Macq.
Researchers find that drug-resistant bacteria can be distinguished from non-resistant bacteria based on structural changes evident in electron microscope images with high accuracy using deep learning.
Combining questions about a person's health with data from smartwatch sensors, a new app can predict within minutes whether someone is infected with COVID-19.
Artificial intelligence-based technique reveals previously unknown cell components that may provide new clues to human development and disease.
A 'new technology shows promise by analyzing images of suspicious-looking lesions and quickly producing a detailed, microscopic image of the skin, bypassing several standard steps typically used for diagnosis - including skin biopsy, tissue fixation, processing, sectioning and histochemical staining.
Considerable advances in point-of-care testing (POCT) devices are emerging from lab-on-a-chip platforms, innovations in smartphone-based technology and wearable technology. Cloud-based deep learning systems herald a future revolution.
Type 2 diabetes can be diagnosed with a whole-body magnetic resonance imaging (MRI) scan. This is shown by a current study by researchers from the German Center for Diabetes Research, the Institute of Diabetes Research and Metabolic Diseases of Helmholtz Zentrum München at the University of Tübingen, the Max Planck Institute for Intelligent Systems and Tübingen University Hospital. They used…
Researchers at Karolinska Institutet have developed an AI-based tool that improves the diagnosis of breast cancer tumours and the ability to predict the risk of recurrence. The greater diagnostic precision can lead to more personalised treatment for the large group of breast cancer patients with intermediate risk tumours. The results are published in the scientific journal Annals of Oncology.
Decreasing the rate of missed lesions could translate into fewer cases of colon cancer.
When patients undergo an MRI, they are told to lie still because even the slightest movement compromises the quality of the images and can create blurred spots and speckles known as artifacts. Moreover, a long acquisition time is usually required to provide high-quality MRI images. A team of researchers from Washington University in St. Louis has found a new deep learning method that can minimize…
Unsupervised deep learning breaks new ground by predicting the progression of COVID-19 and survival of patients directly from their chest CT images.
