Deep learning

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Article • Diagnosis, prognosis, prediction

AI offers advances in cardiovascular imaging

Artificial Intelligence (AI) is providing numerous opportunities across clinical care in the field of cardiovascular imaging. While challenges remain, AI is being applied in terms of diagnosis and prognosis, defining cardiovascular imaging pathways, and image acquisition and analysis. It can also help cardiologists predict which patients may do well, or which treatments are best applied to those…

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Article • Neurology

Supercomputer helps create 3D synthetic brain models

Scientists are using artificial intelligence (AI) and the Cambridge-1 supercomputer to synthesise artificial 3-D MRI images of human brains and create models that show disease states across various ages and genders. The Synthetic Brain Project is focused on building deep learning models which have been developed by King’s College London (KCL) and NVIDIA data scientists and engineers as part of…

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News • Personalizing treatment

AI can help improve precision radiotherapy

The Netherlands Cancer Institute, University of Amsterdam (UvA), and Elekta will collaborate on the development of new AI strategies for the further improvement of precision radiotherapy. This concerns the personalization of treatment by improving the quality of imaging used during treatment, predicting and accounting for changes in the patient’s anatomy over time, and automatically adapting…

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News • Panic prevention

Drone helps elderly escape from burning nursing homes

A student team at Eindhoven University of Technology (TU/e) has introduced an interactive drone that guides elderly people to the exit during a fire in a nursing home, even before the fire brigade arrives. The Blue Jay Aeden is said to be the first interactive drone in the world that can transmit emotions and can fulfil an important function in saving people's lives.

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News • Deep learning vs Aids

AI app could help diagnose HIV more accurately

Pioneering technology developed by University College London (UCL) and Africa Health Research Institute (AHRI) researchers could transform the ability to accurately interpret HIV test results, particularly in low- and middle-income countries. Academics from the London Centre for Nanotechnology at UCL and AHRI used deep learning (artificial intelligence/AI) algorithms to improve health workers’…

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Article • Workflow optimisation

The potential of AI in breast imaging efficiency

The contribution of Artificial intelligence (AI) has great potential in breast imaging efficiency, Professor Linda Moy MD told attendees at the 2021 Society of Breast Imaging/American College of Radiology (SBI/ACR) Breast Imaging Symposium this April. AI models for breast imaging have focused mainly on the diagnostic classification and detection of breast cancer.

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News • AI-assisted analysis

Prediciting viral infections with microscopy & deep learning

When viruses infect cells, changes in the cell nucleus occur, and these can be observed through fluorescence microscopy. Using fluoresence images from live cells, researchers at the University of Zurich have trained an artificial neural network to reliably recognize cells that are infected by adenoviruses or herpes viruses. The procedure also identifies severe acute infections at an early stage.

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News • Combining common risk factors

Deep learning enables dual screening for cancer and CVD

Heart disease and cancer are the leading causes of death in the United States, and it’s increasingly understood that they share common risk factors, including tobacco use, diet, blood pressure, and obesity. Thus, a diagnostic tool that could screen for cardiovascular disease while a patient is already being screened for cancer has the potential to expedite a diagnosis, accelerate treatment, and…

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News • Robotic navigation

Helping robots find their way in crowded emergency rooms

Computer scientists at the University of California San Diego have developed a more accurate navigation system that will allow robots to better negotiate busy clinical environments in general and emergency departments more specifically. The researchers have also developed a dataset of open source videos to help train robotic navigation systems in the future. The team, led by Professor Laurel Riek…

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News • Incidental findings identification

AI system for brain MRIs could boost workflows

An artificial intelligence (AI)-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a new study. “There are an increasing number of MRIs that are performed, not only in the hospital but also for outpatients, so there is a real need to improve radiology workflow,” said study co-lead author Romane Gauriau, PhD,…

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News • Outcome prediction

Deep learning to maximize lifespan after liver transplant

Researchers from the Canadian University Healh Network (UHN) have developed and validated a deep learning model to predict a patient's long-term outcome after receiving a liver transplant. First of its kind in the field of Transplantation, this model is the result of a collaboration between the Ajmera Transplant Centre and Peter Munk Cardiac Centre (PMCC). The study, published in Lancet Digital…

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Article • At ECR 2021

AI experts tackle organ segmentation and health economics

AI is revamping workflows and experts showed how radiologists can integrate it into their department to improve daily practice and healthcare at ECR. The panel also discussed the health economics side of AI to help radiologists define which products make more economic sense for their department. The session tackled automated organ segmentation, an interesting application for AI in radiology.

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News • Survival prediction

Deep learning may lead to better lung cancer treatments

Doctors and healthcare workers may one day use a machine learning model, called deep learning, to guide their treatment decisions for lung cancer patients, according to a team of Penn State Great Valley researchers. In a study, the researchers report that they developed a deep learning model that, in certain conditions, was more than 71% accurate in predicting survival expectancy of lung cancer…

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Article • AI use in clinical diagnosis

Deep learning tool predicts tumour expression from whole slide images

A deep learning model to predict RNA-Seq expression of tumours from whole slide images was among the industry innovations outlined at the 7th Digital Pathology and AI Congress for Europe. Created by French-American start-up Owkin, the detail of how the company’s HE2RNA model provides virtual spatialization of gene expression was detailed to online delegates by senior translational scientist…

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Article • Applications of machine learning

Training AI to predict outcomes for cancer patients

Predicting cancer outcome could help with a clinical decision regarding a patient’s treatment. In his keynote speech during the online ‘7th Digital Pathology and AI Congress: Europe’, Johan Lundin, Research Director at the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki and Professor of Medical Technology at Karolinska Institute, discussed ‘Outcome and…

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Article • Clinical decision support

AI deep learning of PET/CT images to support NSCLC treatment

A software tool to predict the most effective therapy for non-small cell lung cancer (NSCLC) developed by applying deep learning artificial intelligence (AI) to positron emission tomography/computed tomography (PET/CT) images has been developed by researchers at H. Lee Moffitt Cancer Center and Research Institute in Tampa, Florida. The tool is designed to provide a noninvasive, accurate method to…

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Article • AI-assisted MRI segmentation

Deep learning boost for prostate cancer workflow

Prostate cancer radiotherapy treatments guided by MRI are increasingly being explored to help improve patient outcomes and reduce toxicities after treatment. However, this development is being held back as the MRI approach is labour intensive and requires daily adaptive treatment planning, placing significant additional demands on clinician time and oncology services. To address this, a team of…

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