One of the medical specialties highly hopeful in AI’s potential to guide care is neurosurgery. That’s because patients with traumatic brain injuries often present care teams and family members with an especially thorny decision.
Last week the U.K. government announced plans to pour £250 million (around $301.5 million) into a fledgling AI lab run by the National Health Service (NHS). The work is to focus on advancing medical science in various arenas, including cancer care and dementia. This week the skeptics started weighing in.
Only 51% of consumers feel optimistic or safe when it comes to AI infiltrating the healthcare space in the form of helping providers in diagnostic decision making and care management, according to a recent survey from Blumberg Capital.
Machine learning can accurately predict which patients will not live beyond 30 days after discharge from the ER, giving these patients time to discuss end-of-life care with family members and hospice professionals.
If IBM’s Watson goes down as an early failure of AI in healthcare, the fumble may be recorded as an unforced error made by humans who were determined to position the company as the first serious player on the field.
Patients whose blood glucose levels spike during surgery are at heightened risk for poor overall outcomes. A new AI tool has proven effective at predicting, prior to surgery, which patients will have the problem while under the knife.
AI, blockchain and mHealth apps specific to Big Data are among eight emerging technologies healthcare watchers would do well to keep an eye on, according to a consumer-friendly roundup published Aug. 7 in the Santa Clarita Valley Signal.
An attentive mechanical walking aid developed at Columbia University can help correct the gait of people who are unsure on their feet due to motor-skills challenges. In the process, the cane-like device may also reduce the risk of falls.