Also called personalized medicine, this evolving field makes use of an individual’s genes, lifestyle, environment and other factors to identify unique disease risks and guide treatment decision-making.
Masimo's MightySat Medical is the first FDA-cleared pulse oximeter available to consumers without a prescription, which could disrupt the market for the notoriously inaccurate at-home devices.
MediView’s technologies utilize AR to provide clinicians with 3D “X-ray vision” guidance during minimally invasive procedures and surgeries, while also offering remote collaboration.
A year ago, U.S. military researchers presented an algorithm that can tell an individual how much caffeine to consume, and when, to achieve optimal alertness. Now they’ve turned the technique into a freely available tool for “designing effective strategies to maximize alertness while avoiding excessive caffeine consumption.”
Cancer patients undergoing chemotherapy often share word of their adverse reactions to the drugs in online health forums. Researchers at Stanford have used natural language processing to mine these posts, accurately flagging detrimental side effects well before clinical journals advise caution.
A convolutional neural network has proven better than traditional equations, indexes and scoring systems at predicting which hospitalized patients will face readmission not long after being sent home.
The vast majority of healthcare executives––89%––are experimenting with emerging technologies such as AI, according to Accenture’s Digital Health Technology Vision report.
Using a deep neural network equipped with all patient information relevant to diagnosing adult asthma, researchers in Japan have achieved 98% diagnostic accuracy.
Hoping to encourage interdisciplinary collaboration around Big Data over the next 50 to 100 years, Boston University is preparing to build a 17-story architectural marvel.
Facial recognition technology can be used to monitor sedated patients in intensive care units, alerting healthcare workers when a patient is at risk of accidentally removing a breathing tube or engaging in other risky behavior.
