Engineers have developed the smallest single-chip system that is a complete functioning electronic circuit - and implantable chip visible only in a microscope.
Researchers have experimentally demonstrated a novel cancer diagnosis technique based on the scattering of circularly polarized light.
Researchers have proposed that wearable devices could be used to develop a network of health data about a patient, allowing for early diagnosis of COVID-19, even when the patient is asymptomatic.
Researchers have created a machine learning model that helps identify bipolar disorder at earlier stages.
Researchers have developed a novel skin-mounted sticker that absorbs sweat and then changes color to provide an accurate, easy-to-read diagnosis of cystic fibrosis within minutes.
Scientists have designed a portable 3D imaging device which will improve the treatment and diagnosis of cancer.
Using AI and mobile digital microscopy, researchers hope to create screening tools that can detect precursors to cervical cancer in women in resource-limited settings.
Researchers have found that out of the more than 300 COVID-19 machine learning models are not suitable for detecting or diagnosing COVID-19 from standard medical imaging.
Researchers have developed a biobattery-powered device capable of both delivering large molecule pharmaceuticals across the skin barrier and extracting interstitial fluid for diagnostic purposes.
Researchers at the Indian Institute of Science and SigTuple Technologies have developed a method to measure hemoglobin levels in small-volume blood samples.
Deep learning-based system enables dermatologist-level identification of suspicious skin lesions from smartphone photos, allowing better screening.
Scientists have created a new way to detect the proteins that make up the pandemic coronavirus, as well as antibodies against it.
A machine learning system learns on the job. By continuously adapting to new data inputs, this “liquid network” could aid decision-making in medical diagnosis.