Lifeboat Foundation

The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Although there are many instances in which AI can perform healthcare tasks as well or better than humans, implementation factors will prevent large-scale automation of healthcare professional jobs for a considerable period. Ethical issues in the application of AI to healthcare are also discussed.

KEYWORDS: Artificial intelligence, clinical decision support, electronic health record systems.

Artificial intelligence (AI) and related technologies are increasingly prevalent in business and society, and are beginning to be applied to healthcare. These technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer and pharmaceutical organisations.

Fear of being judged appears to be a major obstacle preventing workers from using AI.

A pair of breaches have hit media giant Paramount Global and fashion purveyor Forever 21, exposing personally identifiable information for thousands of people in the latter’s case and setting them up for a raft of follow-on attacks.

In Paramount’s case, the Hollywood bigwig disclosed in a data breach notification letter obtained by media that cyberattackers accessed PII for certain individuals for a month, between May and June of this year. The data included names, birthdates, Social Security numbers, driver’s license numbers, passport numbers, and “information related to [the individual’s] relationship with Paramount.”

It’s unclear if the data pertains to website members, employees, customers, or other profiles — or how many are affected. The data breach notification letter, penned by an operations executive at Nickelodeon Animation Studio, did not elaborate.

“It’s a time of huge uncertainty,” says Geoffrey Hinton from the living room of his home in London. “Nobody really knows what’s going to happen … I’m just sounding the alarm.”

In The Godfather in Conversation, the cognitive psychologist and computer scientist ‘known as the Godfather of AI’ explains why, after a lifetime spent developing a type of artificial intelligence known as deep learning, he is suddenly warning about existential threats to humanity.

Continue reading “The Godfather in Conversation: Why Geoffrey Hinton is worried about the future of AI” »

A new study in Lancet Digital Health identifies early warning symptoms like chest pain and dyspnea that are moderately associated with imminent sudden cardiac arrest. The research suggests that future digital technologies could combine these symptoms with biometric data to more precisely predict and potentially prevent these life-threatening events.

Federal agencies will send the alerts on Oct. 4 to ensure that the country is prepared to inform the public in the event of a large-scale emergency.

Some metals display an unusually high electrical resistance. Researchers now have an explanation for why.

A liquid droplet pushed by the wind contracts and stretches its way along a surface until it breaks apart.

A new symmetry-based classification could help researchers describe open, many-body quantum systems that display quantum chaos.

The quest for understanding quantum systems of many particles—and the exotic phenomena they display—fascinates theorists and experimentalists alike, but it’s one with many hurdles. The number of the system’s quantum states increases exponentially with size; these states are hard to prepare, probe, and characterize in experiments, and interactions with the environment “open” the system, further increasing the number of states to consider. As a result, open, many-body quantum systems remain a frontier of exploration in physics, for which researchers haven’t developed a systematic theoretical framework. A new study by Kohei Kawabata of Princeton University and colleagues has taken an important step toward developing such a general framework by offering a complete classification of these systems based on symmetry principles [1] (Fig. 1).