AI

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Immune cell monitoring

AI could predict risk of lung cancer recurrence

Computer scientists working with pathologists have trained an artificial intelligence (AI) tool to determine which patients with lung cancer have a higher risk of their disease coming back after treatment. The AI tool was able to differentiate between immune cells and cancer cells, enabling researchers to build a detailed picture of how lung cancers evolve in response to the immune system in…

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From physical to computational staining

Deep learning accurately stains digital biopsy H&E slides

Tissue biopsy slides stained using hematoxylin and eosin (H&E) dyes are a cornerstone of histopathology, especially for pathologists needing to diagnose and determine the stage of cancers. A research team led by MIT scientists at the Media Lab, in collaboration with clinicians at Stanford University School of Medicine and Harvard Medical School, now shows that digital scans of these biopsy…

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Lesion differentiation

AI successfully identifies different types of brain injuries

Researchers have developed an AI algorithm that can detect and identify different types of brain injuries. The researchers, from the University of Cambridge and Imperial College London, have clinically validated and tested the AI on large sets of CT scans and found that it was successfully able to detect, segment, quantify and differentiate different types of brain lesions. Their results,…

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Coronavirus imaging

AI enhanced lung ultrasound for COVID-19 testing

Establishing whether a patient is suffering from severe lung disease, possibly COVID-19, within a few minutes: this is possible using fairly simple ultrasound machines that are enhanced with artificial intelligence. A research team at Eindhoven University of Technology (TU/e) and the University of Trento in Italy has been able to translate the expertise of top lung specialists into a software…

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Algorithm-assisted diagnostics

AI in imaging: not as reliable as you'd think

Machine learning and AI are highly unstable in medical image reconstruction, and may lead to false positives and false negatives, a new study suggests. A team of researchers, led by the University of Cambridge and Simon Fraser University, designed a series of tests for medical image reconstruction algorithms based on AI and deep learning, and found that these techniques result in myriad…

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Better tissue discrimination, lower radioation dose

Improving image quality of CT scans

Computed tomography (CT) is one of the most effective medical tests for analysing the effects of many illnesses, including COVID-19, on the lungs. An international team led by the Universitat Oberta de Catalunya (UOC) has developed a new method that improves the quality of the images obtained from CT scans. The algorithm, which has been tested on simulated data, enables them to distinguish…

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Symptom study app

AI diagnostic to predict COVID-19 without testing

Researchers at King’s College London, Massachusetts General Hospital and health science company ZOE have developed an artificial intelligence (AI) diagnostic that can predict whether someone is likely to have COVID-19 based on their symptoms. Their findings are published in Nature Medicine. The AI model uses data from the COVID Symptom Study app to predict COVID-19 infection, by comparing…

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A more integrative approach to digital pathology

imCMS: The door to simple, cheap, reliable bio-stratification

Bringing molecular and digital pathology closer together through a more integrative approach can lead to clear advantages for diagnostic and research workflows. During the recent Digital Pathology and AI Congress (London) and in his keynote presentation ‘Molecular and digital pathology - the value of an integrative approach’ Professor Viktor Koelzer explored the benefits and paid particular…

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Estimating the 'Deep-Replicability' of scientific findings

AI speeds up search for COVID-19 treatments and vaccines

Researchers at Northwestern University are using artificial intelligence (AI) to speed up the search for COVID-19 treatments and vaccines. The AI-powered tool makes it possible to prioritize resources for the most promising studies — and ignore research that is unlikely to yield benefits. In the midst of the pandemic, scientific research is being conducted at an unprecedented rate. The Food and…

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ECG algorithm

New AI tool for cardiac diagnostics

Artificial intelligence (AI) may be an aid to interpreting ECG results, helping healthcare staff to diagnose diseases that affect the heart. Researchers at Uppsala University and heart specialists in Brazil have developed an AI that automatically diagnoses atrial fibrillation and five other common ECG abnormalities just as well as a cardiologist. The study has been published in Nature…

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Imaging collaboration

AI quantifies COVID-19 in chest CT images

Hospitals and organizations worldwide joined forces with AI imaging company icometrix in a global initiative to leverage artificial intelligence (AI) in the fight against COVID-19. The multinational collaboration resulted in the development of an AI algorithm, icolung, which received CE-marking for clinical use in Europe. icolung is the first CE-marked AI solution for CT resulting from a…

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Coronavirus analysis

AI-generated design blueprints for SARS-CoV-2 vaccines published

NEC Corporation announced analysis results from efforts using AI prediction platforms to design blueprints for SARS-CoV-2 vaccines that can drive potent T-cell responses in the majority of the global population. This initiative by the scientific teams within the NEC Group to help combat outbreaks of COVID-19 and support international vaccine development efforts is led by NEC OncoImmunity (NOI) in…

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Medical imaging

SymphonyAI acquires TeraRecon

SymphonyAI Group, an operating group of leading business-to-business AI companies, announced the acquisition of TeraRecon, the market-leading advanced visualization and AI solution provider for medical imaging. As SymphonyAI Group’s seventh portfolio company, TeraRecon has a charter to establish a new portfolio of healthcare AI solutions focused on medical imaging. Using newly patented AI and…

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Experts express doubts

AI outperforming doctors: hype, exaggeration or fact?

Many studies claiming that artificial intelligence (AI) is as good as (or better than) human experts at interpreting medical images are of poor quality and are arguably exaggerated, posing a risk for the safety of ‘millions of patients’ warn researchers in The BMJ. Their findings raise concerns about the quality of evidence underpinning many of these studies, and highlight the need to improve…

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Flu forecast

Portable AI device predicts outbreaks based on coughing

University of Massachusetts Amherst researchers have invented a portable surveillance device powered by machine learning – called FluSense – which can detect coughing and crowd size in real time, then analyze the data to directly monitor flu-like illnesses and influenza trends. The FluSense creators say the new edge-computing platform, envisioned for use in hospitals, healthcare waiting rooms…

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Bringing AI to the clinics

Pioneering a vendor neutral AI system

Capturing all the possibilities brought by AI long-seemed a faraway dream for hospitals, since most artificial intelligence (AI) solutions are vendor dependent, thus complicating their deployment in clinical practice. However, the dream has become reality at Utrecht UMC, which launched a pioneering AI infrastructure able to monitor information and run any algorithm from its HIS, RIS and PACS.…

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Smart algorithm

Automated analysis of whole brain vasculature

Diseases of the brain are often associated with typical vascular changes. Now, scientists at LMU University Hospital Munich, Helmholtz Research Centre for Environmental Health and the Technical University of Munich (TUM) have come up with a technique for visualising the structures of all the brain's blood vessels – right down to the finest capillaries – including any pathological changes. So…

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Professor questions essential artificial intelligence safety

Facing facts: AI in clinical practice

Examining the safety of AI integration into clinical workflow during at the British Institute of Radiology (BIR) annual congress in London, this November, Professor Nicola Strickland focused on issues of data quantity and quality, regulation, validation and testing of algorithms. She also urged radiologists and computer scientists to work more closely together to develop safe, effective and…

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Assessment of brain tumour treatment response

Developing AI algorithms for earlier glioblastoma detection

Novel advanced imaging biomarkers are being developed in a series of studies at several UK centres that may lead to the earlier assessment of treatment response to glioblastoma (GBM) and a better survival rate. Through a number of clinical trials – and the application of artificial intelligence (AI) to retrospective data sets – the aim is to highlight approaches that will enable clinicians to…

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Potentials and pitfalls for IB development

Imaging biomarkers: Close surveillance is mandatory

Imaging biomarkers (IB) have advanced tremendously since first described 25 years ago, but many challenges still block their widespread use. During the EuSoMII’s annual meeting in Valencia, Dr Ángel Alberich-Bayarri gave pragmatic solutions to tackle current bottlenecks and explained why close surveillance is mandatory for further development of IB. However, these need close surveillance with…

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Machine learning in intensive care

AI can predict circulatory failure in ICU

Researchers at ETH Zurich and Inselspital, Bern University Hospital, have developed a method for predicting circulatory failure in patients in intensive care units (ICU) – enabling clinicians to intervene at an early stage. Their approach uses machine learning methods to evaluate an extensive body of patient data. Patients in a hospital’s ICU are kept under close observation: clinicians…

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At-home testing for COVID-19

Coronavirus testing? There's an app for that

A coronavirus app coupled with machine intelligence will soon enable an individual to get an at-home risk assessment based on how they feel and where they’ve been in about a minute, and direct those deemed at risk to the nearest definitive testing facility, investigators say. It will also help provide local and public health officials with real time information on emerging demographics of those…

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