Machine learning

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Clinical computational tools

Managing cancer more effectively

Computational approaches are being applied on enormous amounts of data from sequencing technologies to develop tools to help clinicians manage cancer more effectively.

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Machine learning vs. NSCLC

AI to improve post-treatment surveillance of lung cancer patients

Artificial intelligence (AI) could help guide the post-treatment surveillance of non-small cell lung cancer (NSCLC) patients and improve outcomes as a result, according to a new study.

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Gait analysis

Precise motion capture system to aid in physiotherapy

The motion capture technology called Precise Marker-less could aid doctors and physiotherapists in their consultations and diagnoses for patients in need of rehabilitation.

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Machine learning

AI-enabled exoskeleton aids users with mobility impairments

Scientists have utilized the integration of lightweight material engineering and artificial intelligence to create an exoskeleton robot that can aid those with mobility impairments.

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Machine learning

Using Raman spectroscopy and AI for SARS-CoV-2 detection

Researchers have developed a noninvasive and reagent-free technique for the efficient detection of COVID-19.

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Underrepresentation of women

Machine learning fixes gender bias in clinical trials

Researchers from Israel have developed a technology that rectifies the effects of underrepresentation of women in clinical trials using machine learning models.

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Pregnancy imaging

Machine learning predicts placenta health from MRI scans

Machine learning methods are being used to predict the health of the placenta from a 30-second MRI scan. Researchers hope the approach will offer an insight into the health of expectant mothers and unborn babies by detecting the early signs of dangerous conditions such as pre-eclampsia. Researchers from the School of Biomedical Engineering & Imaging Sciences at King’s College London (KCL)…

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Blood clots in the legs

Machine learning algorithm to diagnose deep vein thrombosis

A team of researchers are developing the use of an artificial intelligence (AI) algorithm with the aim of diagnosing deep vein thrombosis (DVT) more quickly and as effectively as traditional radiologist-interpreted diagnostic scans, potentially cutting down long patient waiting lists and avoiding patients unnecessarily receiving drugs to treat DVT when they don’t have it.

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Biological image analysis

Machine learning accelerates super-resolution microscopy

Scientists use super-resolution microscopy to study previously undiscovered cellular worlds, revealing nanometer-scale details inside cells. This method revolutionized light microscopy and earned its inventors the 2014 Nobel Prize in Chemistry. In an international collaboration, AI researchers from Tübingen have now developed an algorithm that significantly accelerates this technology.

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Diagnosis, prognosis, prediction

AI offers advances in cardiovascular imaging

Artificial Intelligence (AI) is providing numerous opportunities across clinical care in the field of cardiovascular imaging. While challenges remain, AI is being applied in terms of diagnosis and prognosis, defining cardiovascular imaging pathways, and image acquisition and analysis. It can also help cardiologists predict which patients may do well, or which treatments are best applied to those…

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Cardiology & AI

Machine learning to predict sudden cardiac death

Could machine learning (ML) help to predict sudden cardiac death (SCD)? According to Dr Sanjiv Narayan, Professor of Medicine at Stanford University, California, many exciting studies are using ML to predict sudden death in ways not previously possible. ‘Complex data, such as MRI geometry, very large electronic health records or continuous data streams from wearables, are difficult to probe…

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Tool to identify tumour mutations

Machine learning fuels personalised cancer medicine

The Biomedical Genomics laboratory at the Institute for Research in Biomedicine (IRB) Barcelona has developed a computational tool that identifies cancer driver mutations for each tumour type. This and other developments produced by the same lab seek to accelerate cancer research and provide tools to help oncologists choose the best treatment for each patient. The study has been published in the…

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Intensive care & AI

Machine learning model predicts ICU patients' mortality risk

A research team at Universitat Autònoma de Barcelona (UAB), in collaboration with the Hospital de Mataró, developed a new machine learning-based model that predicts the risk of mortality of intensive care unit patients according to their characteristics. The research was published in the latest edition of the journal Artificial Intelligence in Medicine, with a special mention as a…

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Connectome analysis

Machine learning improves prediction of stroke recovery

An international team of scientists led by EPFL has developed a system that combines information from the brain’s connectome – the “wiring” between neurons – and machine learning to assess and predict the outcome of stroke victims. When blood flow to the brain is somehow reduced or restricted, a person can suffer what we know as a stroke (from “ischemic stroke” in medical jargon).…

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