Child Brain Tumours can be Classified by Advanced Imaging and AI

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Research
25 February 2021
Diffusion weighted imaging and machine learning can successfully classify the diagnosis and characteristics of common types of paediatric brain tumours a UK-based multi-centre study, including WMG at the University of Warwick has found. This means that the tumour can be characterised and treated more efficiently.

The largest cause of death from cancer in children are brain tumours in a particular part of the brain, called the posterior fossa.

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New AI Tool can Thwart Coronavirus Mutations

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Research
24 February 2021
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.

Using artificial intelligence (AI), the research team at the USC Viterbi School of Engineering developed a method to speed the analysis of vaccines and zero in on the best potential preventive medical therapy.

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Location Tracking Apps and Privacy Implications

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Research
19 February 2021
How much personal information can our phone apps gather through location tracking? To answer this question, two researchers - Mirco Musolesi (University of Bologna, Italy) and Benjamin Baron (University College London, UK) - carried out a field study using an app specifically developed for this research.
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A Machine-Learning Approach to Finding Treatment Options for COVID-19

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Research
16 February 2021
When the COVID-19 pandemic struck in early 2020, doctors and researchers rushed to find effective treatments. There was little time to spare. "Making new drugs takes forever," says Caroline Uhler, a computational biologist in MIT's Department of Electrical Engineering and Computer Science and the Institute for Data, Systems and Society, and an associate member of the Broad Institute of MIT and Harvard.
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Computational Medicine - Moving from Uncertainty to Precision

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Research
11 February 2021
Individual choices in medicine carry a certain amount of uncertainty.

An innovative partnership at The University of Texas at Austin takes aim at medicine down to the individual level by applying state-of-the-art computation to medical care.

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Wearable Devices can Detect COVID-19 Symptoms and Predict Diagnosis

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Research
09 February 2021
Wearable devices can identify COVID-19 cases earlier than traditional diagnostic methods and can help track and improve management of the disease, Mount Sinai researchers report in one of the first studies on the topic. The findings were published in the Journal of Medical Internet Research on January 29.
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Researchers Develop Data Tool that may Improve Care

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Research
08 February 2021
With the aid of sophisticated machine learning, researchers at UPMC and the University of Pittsburgh School of Medicine demonstrated that a tool they developed can rapidly predict mortality for patients facing transfer between hospitals in order to access higher-acuity care. This research, published today in PLOS One, could help physicians, patients and their families avoid unnecessary hospital transfers and low-value treatments, while better focusing on the goals of care expressed by patients.
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More eHealth News ...

  1. New Neural Network Enables Easy Screening of Sleep Apnoea in Patients with Cerebrovascular Disease
  2. COVID-19 Warnings Were on Twitter Well Before the Outbreak of the Pandemic
  3. Using Artificial Intelligence to Find New Uses for Existing Medications
  4. One in Four Doctors Attacked, Harassed on Social Media
  5. New Virtual Screening Strategy Identifies Existing Drug that Inhibits COVID-19 Virus
  6. Significant Disparities in Telemedicine Use, Especially Among Older and Non-White Patients
  7. Model Used to Evaluate Lockdowns was Flawed
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