AI sees and hears COVID-19 in your lungs
Two deep learning algorithms that identify patterns of COVID-19 in lung images and breath sounds, may help in the fight against other respiratory diseases and the growing challenge of antibiotic resistance.
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3D printed device to treat middle ear infections
Researchers have designed a miniaturized 3D-printed device to inactivate Pseudomonas aeruginosa, a common bacterium that causes the infection.
Photos of toasters train AI to detect COVID
Research using machine learning on images of everyday items is improving the accuracy and speed of detecting respiratory diseases, reducing the need for specialist medical expertise.
Decentralized patient monitoring: Sensors quickly detect changes in vital signs
The Fraunhofer Institutes project M³Infekt aims to develop a multi-modal, modular and mobile system of sensors for monitoring infectious diseases.
AI accurately detects COVID-19 on chest x-rays
Researchers have developed a new AI platform that detects COVID-19 by analyzing X-ray images of the lungs.
AI model detects Covid-19 infections through coughs
Researchers have found that people who are asymptomatic for Covid-19 may differ from healthy individuals in the way that they cough.
5 ways AI is used against COVID-19
Find out more about how scientists and physician are using AI to make contributions in the fight against the coronavirus.
'Smart' breathalizer can reveal lung disease
Using specialized nanoparticles, engineers have developed a way to monitor pneumonia or other lung diseases by analyzing the breath exhaled by the patient.
High-tech clothing: Wearable health
Thanks to a variety of smart technologies, high-tech clothing today is capable of analyzing body functions or actively optimizing the microclimate.
mhealth: A portable ultrasound scanner for COVID-19
Researchers are collaborating with local partners to establish a network of portable, handheld ultrasound scanners that can soon accelerate COVID-19 diagnosis.
Using machine learning to detect COVID-19 in X-rays
Students at Cranfield University have designed computer models that can identify COVID-19 in X-rays.
AI enables rapid ultrasound COVID-19 testing
Establishing whether a patient is suffering from COVID-19 within a few minutes is possible using ultrasound machines that are enhanced with artificial intelligence.
Ultrasound for space offers remote diagnosis to patients on Earth
Radiologists are investigating people's medical conditions and pregnancies remotely thanks to an ESA-backed robotic technology.
AI distinguishes pneumonia from COVID-19
Researchers have developed a predictive artificial intelligence model that can tell the difference between healthy patients, those who are ill with pneumonia and those who have COVID-19, from chest X-rays.
AI could serve as backup to radiologists' eyes
A study showed that an AI algorithm provides results comparable with lung function tests, which measure how forcefully a person can exhale.
Device could support multiple COVID-19 patients from one ventilator
3D printing fuels efforts to rapidly increase ventilator capacity while providing each patient on vent support with individually tailored gas pressures and pressure monitoring.
In-ear sensors to help in fight against COVID-19
Scientists plan to use high-tech biometric sensors for 24-hour monitoring of COVID-19 patients in home isolation.
Sensors could offer early detection of lung tumors
Researchers have developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease.
AI, App provide at-home assessment of coronavirus risk
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.
Sensor fusion device for non-contact measurement of vital signs
A researcher has developed a multiple sensor fusion device for non-contact measurement of vital signs and its clinical applications.
“CheXNeXt” outperformed radiologists in evaluating chest X-rays
In a matter of seconds, a new algorithm read chest X-rays for 14 pathologies, performing as well as radiologists in most cases, a Stanford-led study says.
“Hive mind” outperforms a single doctor or AI
A "Hive Mind" of doctors, moderated by AI algorithms, makes more accurate diagnoses than the doctors or machine learning alone, according to a new study from Stanford and Unanimous AI.
AI quickly and accurately diagnoses eye diseases
Using machine learning, researchers have developed a new computational tool to screen patients with common but blinding retinal diseases, potentially speeding diagnoses and treatment.