News • Deep learning analysis of X-rays
AI used to triage patients with chest pain
Artificial intelligence (AI) may help improve care for patients who show up at the hospital with acute chest pain, according to a new study published in Radiology.
AI
Article • Centralised image library and archive
From regional to national: digital pathology network transformation
Transforming a regional digital pathology network into a national programme across the UK has the potential to save the NHS around £100m a year. Such a network – one that sees a centralised digital pathology image library and archive, as opposed to individual hospitals having their own infrastructure and teams to manage it – can also offer a range of other benefits alongside significant cost…
News • Glycemia assessment
Using machine learning to predict poor glycemic control in patients with type 2 diabetes
The risk for poor glycemic control in patients with type 2 diabetes can be predicted with confidence by using machine learning methods, a new study from Finland finds.
News • Deep learning, infrared and 3D videos
Using AI to classify epileptic seizures
A team of researchers from Portugal and Germany tested an innovative solution to classify seizures, the main symptom of epilepsy, using infrared radar and 3D videos.
News • Hereditary non-polyposis colorectal cancer
Lynch syndrome: AI improves colorectal cancer screening
Researchers have now found that artificial intelligence (AI) can improve the effectiveness of colonoscopy in the presence of Lynch syndrome.
News • Application in pathology
Endometrial cancer diagnostics: AI gives new insights
New research shows the power of artificial intelligence (AI) applied to endometrial carcinoma microscopy images. This could improve diagnosis and treatment of uterine cancer.
Article • Image augmentation, interpretation and evaluation
AI in multimodality hybrid imaging: a diamond in the rough
AI-based models for multimodality hybrid imaging have the potential to be a potent clinical tool but are currently held back by a lack of transparency and maturity, says Dr Irène Buvat, from the Laboratory of translational Imaging in Oncology, Institute Curie in Paris, France.
News • Prevention of unnecessary treatments and examination
AI detects early signs of osteoarthritis from x-ray images
Researchers from the University of Jyväskylä and the Central Finland Health Care District have developed an AI based neural network to detect an early knee osteoarthritis from x-ray images.
News • Machine learning approach for screening
AI model predicts results of Covid-19 tests
A new study demonstrates that AI models, using symptom and demographic features, can help predict Covid-19 infections, providing a way for rapid screening and cost-effective infection detection.
News • Enhancing diagnostics
Al and robots could help detect urinary tract infections early
Scientists are developing artificial intelligence (AI) and talking robots to help to detect urinary tract infections (UTIs) in vulnerable people early.
News • AI enables greater mobility
Personalized finger joint implants from a 3D printer
Researchers use AI to develop personalized 3D-printed joint implants so that these delicate finger parts can be replaced when necessary (e.g. after illness or injury).
Sponsored • Digital solutions for radiology
How to accelerate healthcare innovation in AI
Tapping the thriving Radiology AI ecosystem, Bayer recently announced three collaboration agreements for its digital platform, Calantic Digital Solutions, as well as an AI accelerator program.
Article • Radiology & artificial intelligence
How to integrate AI in the clinical workflow: 7 lessons
In radiology, it is not about if but about when artificial intelligence (AI) will be used, said Professor Dr Tim Leiner of Utrecht University Medical Center at this year’s European Congress of Radiology in Vienna. For all those who are new to AI, the Dutch radiologist gave an overview of the lessons he and his team have learnt so far.
Article • The role of the radiographer
AI in radiation protection: a potential game changer
Radiographers could help design new artificial intelligence (AI) tools for radiation protection, Mark McEntee, professor of diagnostic radiography at University College Cork, Ireland, argued during the annual EuSoMII meeting in October.
Article • Assistance and decision-making systems
Artificial intelligence for preoperative planning
In surgery, artificial intelligence (AI) is applied mostly in imaging, navigation, and robotic intervention. However, AI can also play a major role in preoperative planning. Objective decisions-making, optimal utilisation of operating theatres and less overtime are additional advantages that are achieved with the use of AI in surgery.
Article • AI-based personalized medical care
I³lung: EU launches lung cancer initiative
This summer, The European Commission launched I3lung, a new research initiative as a part of Horizon Europe, the EU’s research and innovation program. This research initiative aims to create a cutting-edge, decision-making tool to help clinicians and patients select the best lung cancer treatment based on each patient’s specific needs and circumstances.
Article • Regulatory challenges for AI-based diagnostics
Further IVDR changes: a step in the right direction, but…
New changes made to the timetable for the In vitro Diagnostic Medical Device Regulation (IVDR) across Europe could have a significant impact on manufacturers and users, an expert points out. While the extension of the transition period was a welcome step, other changes which were hoped for remain painfully absent.
Article • Visceral imaging
Endosonography: AI takes on the “supreme discipline”
Endosonography poses unique challenges for medical professionals, because two demanding disciplines have to be mastered at the same time. The use of artificial intelligence (AI) could help speed up the notoriously slow learning curve of the procedure, says Prof Dr Christoph F. Dietrich. At the Visceral Medicine Congress in Hamburg, the expert explained how AI can help endosonography achieve…
Article • Targeted Real-time Early Warning System for hospitals
Early detection of sepsis with the help of AI
Sepsis, a life-threatening, systemic, toxic bodily reaction to infection, is often difficult to detect in its early stages. Its symptoms, including fever, shortness of breath, rapid heart rate, and confusion, are associated with many medical conditions of hospitalized patients. But if not treated rapidly, a patient may die. The Targeted Real-time Early Warning System (TREWS) for sepsis detection…
Article • Imaging advances
Liver disease assessment: AI may give CT the edge over MRI
To assess diffuse liver disease, MRI is currently the modality of choice. New developments in artificial intelligence (AI) could tip the scales in favour of CT imaging. At ECR 2022 in July, experts showed how AI technology enables CT to quantify liver fat as exquisitely as MRI.
Article • Diagnostic assistant systems
AI in endoscopy: helper, trainer – influencer?
Artificial intelligence (AI) is increasing its foothold in endoscopy. Although the algorithms often detect pathologies faster than humans, their use also generates new problems. PD Dr Alexander Hann from the University Hospital Würzburg points out that the use of AI helpers can affect not only the reporting of findings – but also the person making the findings.
Malignant tumour management
’Our machine learning model achieved 88.9% accuracy in predicting the sarcoma-specific survival rate’
Clinical management of soft tissue sarcoma is particularly challenging. Dr Sebastian Foersch, researcher at the Institute of Pathology at the University Medical Center in Mainz, Germany, has used a deep learning model for diagnosis and prognosis prediction of soft tissue sarcoma using conventional histopathology slides.
CNN applications in pathology
‘Deep learning can predict survival directly from histology in clear cell renal cell carcinoma’
Renal cell carcinoma is among the fifteen most common cancers worldwide. Dr Titus Brinker, from the German Cancer Research Center (DKFZ), looked at whether a convolutional neural network (CNN) can extract relevant image features from a typical H&E-stained slide to predict 5-year overall survival.
Article • AI provides prognostic information
Next-generation deep learning models predict cancer survival
Deaths from cancer are currently estimated at 10 million each year worldwide. Conventional cancer staging systems aim to categorize patients into different groups with distinct outcomes. ‘However, even within a specific stage, there is often substantial variation in patient outcomes,’ Markus Plass, academic researcher from the Medical University of Graz, Austria, explained to Healthcare in…
Supervised learning approach
A new deep learning-based algorithm to predict relapse-free survival in papillary thyroid carcinoma
The tall cell variant (TCV) is an aggressive subtype of papillary thyroid carcinoma (PTC). Sebastian Stenman, researcher from the Institute for Molecular Medicine, and the Department of Pathology at the University of Helsinki, Finland, is developing and training a deep learning algorithm using supervised learning to detect and quantify the proportion of tall cells in PTC.