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…
"Given the rapid transition towards digitisation, digital pathology is now unquestionably the future", reports pathologist Dr Talat Zehra from Pakistan. "However, some pathologists, particularly in underdeveloped countries, are still reluctant to accept its place in their labs. Among their many reasons, some feel that histopathology is a very complex and subjective field and…
Researchers in Oxford have developed a machine learning algorithm that could significantly improve clinicians’ ability to identify hospitalised patients whose condition is deteriorating to the extent that they need intensive care. The HAVEN system (Hospital-wide Alerting Via Electronic Noticeboard) was developed as part of a collaboration between the University of Oxford’s Institute of…
A way of using machine learning to more accurately identify patients with a mix of psychotic and depressive symptoms has been developed by researchers at the University of Birmingham. Patients with depression or psychosis rarely experience symptoms of purely one or the other illness. Historically, this has meant that mental health clinicians give a diagnosis of a ‘primary’ illness, but with…
USC researchers have developed a new method to counter emergent mutations of the coronavirus and hasten vaccine development to stop the pathogen responsible for killing thousands of people and ruining the economy.
In order to detect the Corona virus SARS-CoV-2, there are further methods of diagnosis apart from the globally used PCR tests (Polymerase chain reaction): The infection can also be recognised on CT scans – for which Artificial Intelligence (AI) can be used as well. An AI system can not only filter CT scan of Covid-19 patients from a data set, but also estimate, which areas of the image are of…
Coronavirus-associated concerns dominate the Top 10 list of important technology hazard risks for hospitals, in an annual report published by ECRI, a nonprofit technology Pennsylvania research firm. The list is derived from ECRI’s team of technology experts who monitor hospital and healthcare organizations, and published to inform healthcare facilities about important safety issues involving…
A new EU-wide repository for health-related imaging data could boost development and marketing of AI tools for better cancer management. The open-source database will collect and harmonise images acquired from 40,000 patients, spanning different countries, modalities and equipment. This approach could eliminate one of the major bottlenecks in the clinical adoption of AI today: Data bias.
The Belgian initiative icovid, which supports radiologists in the assessment of CT images of the lungs of COVID-19 patients, has grown into a multicentre European project, co-funded by the EU Horizon 2020 programme. Icovid was set up in March by UZ Brussel, KU Leuven, icometrix and ETRO, an imec research group of VUB.
Prostate cancer is one of the most common cancers among men. Patients are determined to have prostate cancer primarily based on PSA, a cancer factor in blood. However, as diagnostic accuracy is as low as 30%, a considerable number of patients undergo additional invasive biopsy and thus suffer from resultant side effects, such as bleeding and pain.
Artificial intelligence (AI) image reconstruction dramatically reduces magnetic resonance imaging (MRI) scan time, according to new research. The first clinical study comparing AI-accelerated knee MRI scans with conventional scans shows that the AI scans are not only diagnostically interchangeable with conventional ones, but also produce higher quality images. Results of this interchangeability…
Researchers at the Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University have preliminarily validated an artificial intelligence (AI) tool to predict how likely the disease is to recur following surgical treatment for prostate cancer. The tool, called RadClip, uses AI algorithms to examine a variety of data, from MRI scans to molecular…
It is a simple image of two desks in a hospital pathology department, taken a matter of months apart. But there can be few more vivid images that illustrate the changing world of pathology as the specialty forges ahead into the digital era. The image was taken by Dr Solène-Florence Kammerer-Jacquet during the transition towards digital pathology at Rennes University Hospital in France in the…
Predicting the outcome of cancer can help the clinical decision-making process related to a patient’s treatment. The potential for Artificial Intelligence (AI) to support this was a key facet of the final keynote speech to the online 7th Digital Pathology and AI Congress: Europe.
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…
The advent of digital pathology is offering a unique opportunity to develop computerized image analysis methods to diagnose disease and predict outcomes for cancer patients from histopathology tissue sections. Such advances can help predict risk of recurrence, disease aggressiveness and long-term survival, according to a leading expert in the field, Professor Anant Madabhushi from Case Western…
A new generation of tissue microarrays are delivering more efficient and time-effective solutions to answering complex clinical and scientific questions. Sitting at the core of this new approach is digital pathology, allowing specific and targeted analysis of small areas of tissue. Latest developments in the approach were outlined by Professor Inti Zlobec at an online session of the 7th Digital…
Scientists have developed a machine-learning method that crunches massive amounts of data to help determine which existing medications could improve outcomes in diseases for which they are not prescribed. The intent of this work is to speed up drug repurposing, which is not a new concept – think Botox injections, first approved to treat crossed eyes and now a migraine treatment and top cosmetic…
AI can help tackle inequities and bias in healthcare but it also brings partiality issues of its own, experts explained in a Hot Topic session entitled "Artificial Intelligence and Implications for Health Equity: Will AI Improve Equity or Increase Disparities?" at RSNA. Two leading researchers showcased how deep learning may help bring back all the patients into screening mammography…
Doctors at Addenbrooke’s Hospital in Cambridge aim to drastically cut cancer waiting times by using artificial intelligence (AI) to automate lengthy radiotherapy preparations. The AI technology, known as InnerEye, is the result of an eight-year collaboration between researchers at Cambridge-based Microsoft Research, Addenbrooke’s Hospital and the University of Cambridge.
Getting computers to “think” like humans is the holy grail of artificial intelligence, but human brains turn out to be tough acts to follow. The human brain is a master of applying previously learned knowledge to new situations and constantly refining what’s been learned. This ability to be adaptive has been hard to replicate in machines. Now, researchers at the Salk Institute have used a…
Medicus AI announces the successful launch of its first live project under SafePlay, the digital platform supporting rapid antigen testing, which went live in partnership with Roche Diagnostics Germany and 21Dx in Munich this month. Medicus provides operators with a tech-enabled end-to-end solution that supports the logistical aspects of testing, managing the administrative workflow from…
A great deal of solutions using new technologies have been released to help tackle the Covid-19 pandemic and a panel of international experts shared a few examples during the Barcelona Health Summit last October. Contact-tracing apps are an interesting option to manage a pandemic, but the creation process can take a long time and must meet several requirements, according to a Dutch official who…
The deployment of conversational user interfaces (CUI) or chatbots to healthcare has started gaining momentum. It is fueled by the rising power of artificial intelligence (AI), the increasing popularity of mobile health applications as well as the desire for engagement and usability. The past few years have seen a myriad of innovations in chatbots that can automate and engage in human-like…
An Artificial Intelligence test has been shown to be able to rapidly screen patients arriving in Emergency Departments for Covid-19, using clinical information routinely available within the first hour of coming to hospital. Results of the CURIAL study, published in The Lancet Digital Health, show that the AI test correctly predicted the Covid-19 status of 92.3% of patients coming to Emergency…