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…
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…
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…
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…
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.
The U.S. Food and Drug Administration released the agency’s first Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan. This action plan describes a multi-pronged approach to advance the Agency’s oversight of AI/ML-based medical software. “This action plan outlines the FDA’s next steps towards furthering oversight for AI/ML-based SaMD,”…
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.
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…
The sudden spread of COVID-19 in early 2020 has considerably exacerbated the issue as it forced the closure of “non-essential” radiology activities while dramatically increasing the number of patients requiring a scan.
Researchers in Finland have developed a machine learning model that can help us treat cancer more effectively.
Cancer cells spread by switching on and off abilities to sense their surroundings, move, hide and grow new tumors, a new study has found. This sensitivity to their surroundings is the key ability that makes small numbers of cancer cells better at spreading than other cells in a tumor.
A panel of experts from the USA and China highlighted AI use in radiological workflow during the Covid pandemic and identified current pitfalls during the Hot Topic session at RSNA 2020. Radiologists from the USA prioritised Covid articles, delivered quick reviews, made all results open access, and helped organise a white paper from the Fleischner Society recognising recommendations for the role…
Men die about five years earlier than women across the world. As initiatives to boost awareness of men’s health unfolded in November, an international project is bringing the forefront of AI research to tackle prostate cancer (PC), the second most frequent type of cancer in men and the third most lethal in Europe.
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…
Although the Covid-19 pandemic has put wind behind the sails of AI in healthcare, domain specific tools are needed to build and deploy AI and harness its power in data handling, training workflows and reproducibility of state-of-the-art approaches, according to Kimberly Powell, NVIDIA Vice President of Healthcare at the technology firm NVIDIA, presenter of a public address at RSNA 2020.
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…
