Healthcare

Here’s how AI is helping doctors identify and treat sepsis

  • Patients are 20% less likely to die of sepsis because a new AI system catches symptoms hours earlier than traditional methods, new research shows.
  • The system scours medical records and clinical notes to identify patients at risk of life-threatening complications and suggests treatment protocols.
  • In 82% of sepsis cases, the AI was accurate nearly 40% of the time.
  • The system is now being applied to improve outcomes for other illnesses beyond sepsis.

Patients are 20% less likely to die of sepsis because a new AI system catches symptoms hours earlier than traditional methods, new research shows.

The system scours medical records and clinical notes to identify patients at risk of life-threatening complications. The work, which could significantly cut patient mortality from one of the top causes of hospital deaths worldwide, is published in Nature Medicine and Nature Digital Medicine.

“It is the first instance where AI is implemented at the bedside, used by thousands of providers, and where we’re seeing lives saved,” says Suchi Saria, founding research director of the Malone Center for Engineering in Healthcare at Johns Hopkins University, and lead author of the studies, which evaluated more than a half million patients over two years.

“This is an extraordinary leap that will save thousands of sepsis patients annually. And the approach is now being applied to improve outcomes in other important problem areas beyond sepsis.”

Sepsis occurs when an infection triggers a chain reaction throughout the body. Inflammation can lead to blood clots and leaking blood vessels, and ultimately can cause organ damage or organ failure. About 1.7 million adults develop sepsis every year in the United States and more than 250,000 of them die.

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

Veille-cyber

Share
Published by
Veille-cyber

Recent Posts

Bots et IA biaisées : menaces pour la cybersécurité

Bots et IA biaisées : une menace silencieuse pour la cybersécurité des entreprises Introduction Les…

17 heures ago

Cloudflare en Panne

Cloudflare en Panne : Causes Officielles, Impacts et Risques pour les Entreprises  Le 5 décembre…

17 heures ago

Alerte sur le Malware Brickstorm : Une Menace pour les Infrastructures Critiques

Introduction La cybersécurité est aujourd’hui une priorité mondiale. Récemment, la CISA (Cybersecurity and Infrastructure Security…

17 heures ago

Cloud Computing : État de la menace et stratégies de protection

  La transformation numérique face aux nouvelles menaces Le cloud computing s’impose aujourd’hui comme un…

2 jours ago

Attaque DDoS record : Cloudflare face au botnet Aisuru – Une analyse de l’évolution des cybermenaces

Les attaques par déni de service distribué (DDoS) continuent d'évoluer en sophistication et en ampleur,…

2 jours ago

Poèmes Pirates : La Nouvelle Arme Contre Votre IA

Face à l'adoption croissante des technologies d'IA dans les PME, une nouvelle menace cybersécuritaire émerge…

2 jours ago

This website uses cookies.