Background Reports 2021 -- MEDICA - World Forum for Medicine

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Sinonasal cancer: AI facilitates breakthrough in diagnostics


Researchers at LMU and Charité hospital in Berlin have developed a method for classifying difficult-to-diagnose nasal cavity tumors.
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Image: Hands holding a tablet with MRI scans of the brain; Copyright: Nikita_Karchevskyi


Tumors: forecasting the risks of brain surgery


Can surgeons quantify the risk of aphasia when removing a brain tumor? To find out, researchers at Klinikum rechts der Isar of the Technical University of Munich (TUM) are analyzing the brain as a network. In a current study with 60 patients, they already achieved an accuracy rate with three quarters of their predictions.
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Image: A woman sits on a hospital bed while a service robot comes through the door and offers drinks; Copyright: Jasper Block/Robotise

Jasper Block/Robotise

Researchers evaluate robot use in clinical routine


What potential do robotic systems hold when it comes to relieving highly qualified nursing staff in hospitals of non-specialist service activities? This is currently being researched by the Professorship of Nursing Science at the Catholic University of Eichstätt-Ingolstadt (KU) and the LMU university hospital in Munich.
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Laboratory: how smart gadgets support everyday work


At MEDICA 2022, you can see why smart assistants are needed in the laboratory and which gadgets have made it into everyday laboratory work, thus reducing the workload of the specialists there and increasing efficiency.
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MEDICA 2022: Simplifying analysis and visualization of medical image data


A team of researchers from Kaiserslautern and Leipzig is working on a system that automatically analyses and visualises medical data, including their uncertainties.
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Image: A 3D scanner scans a white curved object; Copyright: Fraunhofer IPK / Larissa Klassen

Fraunhofer IPK / Larissa Klassen

MEDICA 2022: Digital hospital made easy


Interoperability, integration, interaction – medical technology is dominated by digitalization. At MEDICA 2022, Fraunhofer IPK will be demonstrating how intelligent linking of devices and systems, including digital twins, will shape processes in the hospital of the future.
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Image: A black haired woman and a bald man analyze an x-ray of a lung; Copyright: University of the West of Scotland

University of the West of Scotland

Artificial intelligence could help ease hospital pressures


Pioneering artificial intelligence (AI) which automatically diagnoses lung diseases – such as tuberculosis and pneumonia – could ease winter pressures on hospitals, University of the West of Scotland researchers believe.
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Image: Mobile laboratory unit with integrated lifting device for a standard truck chassis; Copyright: Fraunhofer IBMT/Markus Michel

Fraunhofer IBMT/Markus Michel

MEDICA 2022: Biological laboratory to go


Researchers from the Fraunhofer Institute for Biomedical Engineering IBMT have developed the “BioSensoLab“, a mobile biological laboratory with which they can demonstrate new developments to customers and test them together – on site at their companies.
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Image: Software for medical back analysis runs on a screen while in the background a shirtless man walks on a treadmill; Copyright: SZB


MEDICA 2022: AI allows personalised diagnosis of back problems


A team of researchers from TU Kaiserslautern (TUK), the University Medical Centre in Mainz and several companies is working on a method that will enable more efficient monitoring of malpositions and strains on the back.
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Doinglab: Nutrition management with AI


Watching your diet based on various health issues can sometimes be tiring. To make the process easier and help patients to monitor their intake, the start-up Doinglab developed an artificial intelligence technology that can recognize and understand food. FoodLens provides detailed information about the food with just a picture.
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Digital technology linking care homes to clinical advice hubs reduces A&E attendances


The use of digital technology in residential care homes can reduce the number of emergency department attendances by 10% each month, according to new research by Lancaster Medical School PhD student Alex Garner.
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Speech as a new diagnostic tool in ALS and FTD


The speech of patients with neurodegenerative diseases gradually changes. Thanks to the help of artificial intelligence, even the slightest changes can become the basis for a diagnosis.
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Image: Two female hands on blue background. On the left with a yellow tracking bracelet and on the right with a smartphone in hand, Copyright: Irina Shatilova

Irina Shatilova

MS: Model predicts health conditions during stay-at-home periods


Research led by Carnegie Mellon University has developed a model that can accurately predict how stay-at-home orders like those put in place during the COVID-19 pandemic affect the mental health of people with chronic neurological disorders such as multiple sclerosis.
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Easy-to-use-tool predicts risk of complications from hysterectomy


Researchers have developed easy-to-use online prediction tools that provide personalized risk estimates for patients undergoing hysterectomy for benign disease.
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Novel sensor system with AI-driven biomarkers for patients with heart failure


UNISONO aims to develop a novel system combining an ear-worn sensor with speech recognition.
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Juntendo University

DryEyeRhythm: A reliable, valid, and non-invasive app to assess dry eye disease


The app – released in 2016 – can be used for the monitoring of dry eye disease and underscores the feasibility of human-centered medicine through apps.
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Asociación RUVID

A tool based on artificial intelligence can automatically detect pathologies in thorax X-rays


A research team has developed a tool for the automatic detection of pathologies in thorax X-rays based on the experience and expertise of radiology staff that are validated from the automatic analysis of medical reports.
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Wearable sensors styled into t-shirts and face masks


Imperial researchers have embedded new low-cost sensors that monitor breathing, heart rate, and ammonia into t-shirts and face masks.
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Using AI during cancer-screening results in more recommended controls


Patients with polyps have a higher risk of evolving cancer in the future. Using Artificial intelligence (AI) during colonoscopy can be useful to detect pre-cancerous polyps, Yuichi Mori, doctor and associate professor from the Clinical Effectiveness Research group at the University of Oslo says.
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Mathematical models help predict the evolution of neurodegenerative diseases


In their latest study, the researchers involved have demonstrated that "integrating and processing all the data together, using multilayer networks, provides a more comprehensive analysis of the data than if they are analysed individually and independently".
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Image: A wearable assistive robot that can detect and prevent a fall before it happens, exhibited in a hall; Copyright: Nanyang Technological University

Nanyang Technological University

Assistive robot to prevent falls and assist in physiotherapy for the elderly


Researchers at Nanyang Technological University, Singapore (NTU Singapore) and Tan Tock Seng Hospital (TTSH) have developed a wearable assistive robot that can detect and prevent a fall before it happens, reducing the user’s risk of sustaining injuries.
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Machine learning to unlock genomic code in clinical cancer samples


A new paper from University of Helsinki, published in Nature Communications, suggests a method for accurately analysing genomics data in cancer archival biopsies.
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Bild: Elderly woman sitting on the bed and having a heart problem, she is holding her chest in pain; Copyright: Rawpixel


AI improves treatment in women with heart attacks


Heart attacks in women are more likely to be fatal than in men. The reasons are differences in age and in comorbidity burden which makes risk assessment in women a challenge. Researchers at the University of Zurich have now developed a novel artificial-intelligence-based risk score that improves personalized care for female patients with heart attacks.
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