Machine learning

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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…

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AI 'Haven' in intensive care

Machine learning to identify deteriorating hospital patients

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…

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Detecting depression, psychosis

Machine learning could aid mental health diagnoses

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…

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Image-based diagnosis of Covid-19

AI detects coronavirus on CT scans

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…

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'Thumbs up' for image reconstruction

Facebook AI accelerates MRI exams

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…

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Applications of machine learning

Training AI to predict outcomes for cancer patients

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…

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Machine learning advances diagnostics and prognostics

Computerized image analysis can predict cancer outcomes

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…

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Drug repurposing

AI finds new uses for existing medications

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…

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"InnerEye" Artificial Intelligence

AI could help cut waiting times for cancer radiotherapy

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.

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Brain tumor treatment network

'Federated learning' AI approach allows hospitals to share patient data privately

To answer medical questions that can be applied to a wide patient population, machine learning models rely on large, diverse datasets from a variety of institutions. However, health systems and hospitals are often resistant to sharing patient data, due to legal, privacy, and cultural challenges. An emerging technique called federated learning is a solution to this dilemma, according to a study…

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Glioma grading

AI enhances brain tumour diagnosis

A new machine learning approach classifies a common type of brain tumour into low or high grades with almost 98% accuracy, researchers report in the journal IEEE Access. Scientists in India and Japan, including from Kyoto University’s Institute for Integrated Cell-Material Sciences (iCeMS), developed the method to help clinicians choose the most effective treatment strategy for individual…

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Identification of skin cancer

Machine learning challenge on melanoma classification

The Society for Imaging Informatics in Medicine (SIIM) and the International Skin Imaging Collaboration (ISIC) are working together to host a machine learning challenge on melanoma classification, using the ISIC archive which contains the largest publicly available collection of quality controlled dermoscopic images of skin lesions. Image contributors include: Hospital Clínic de Barcelona,…

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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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Corona-induced coughing

New app listens to the 'sounds of COVID-19'

A new app, which will be used to collect data to develop machine learning algorithms that could automatically detect whether a person is suffering from COVID-19 based on the sound of their voice, their breathing and coughing, has been launched by researchers at the University of Cambridge. The COVID-19 Sounds App is now available as a web app for Chrome and Firefox browsers. Versions for Android…

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Oncology breakthrough

Blood test detects 50+ cancer types, often before symptoms show

Researchers have developed the first blood test that can accurately detect more than 50 types of cancer and identify in which tissue the cancer originated, often before there are any clinical signs or symptoms of the disease. In a paper published in the leading cancer journal Annals of Oncology, the researchers show that the test, which could eventually be used in national cancer screening…

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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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The science of sleep

AI could enhance diagnosis and treatment of sleep disorders

Artificial intelligence (AI) has the potential to improve efficiencies and precision in sleep medicine, resulting in more patient-centered care and better outcomes, according to a new position statement from the American Academy of Sleep Medicine. Published in the Journal of Clinical Sleep Medicine, the position statement was developed by the AASM’s Artificial Intelligence in Sleep Medicine…

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Blood test & AI power

Early brain tumour detection – within minutes

A simple blood test coupled with artificial intelligence (AI) analysis could help spot the signs of a brain tumour sooner in patients. Brain tumour diagnosis is difficult: patients often see their family doctor (GP) several times before referral for a scan. However, research presented at the 2019 National Cancer Research Institute (NCRI) Cancer Conference in Glasgow last November suggests the…

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Decision support

AI can predict septic shock

Researchers at Linköping University (LiU) have developed an algorithm that can identify patients at a higher risk of septic shock, a life-threatening condition that is difficult for doctors to predict. At the same time, it is important to recognise the symptoms as early as possible, since early treatment increases the chance of survival. A group of LiU researchers is using artificial…

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MRI & machine learning

A look into the genome of brain tumors

Researchers at Osaka University have developed a computer method that uses magnetic resonance imaging (MRI) and machine learning to rapidly forecast genetic mutations in glioma tumors, which occur in the brain or spine. The work may help glioma patients to receive more suitable treatment faster, giving better outcomes. The research was recently published in Scientific Reports. Cancer treatment…

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