Healthcare Trends to Watch in 2025: AI and Technology Developments
Healthcare trends in 2025 will focus on AI's operational role, a tech reassessment, and enhanced care management. 🏥🤖📈
Reliability of generative artificial intelligence in identifying the major risk factors for venous thrombosis.
We reviewed a study on AI's reliability in identifying venous thrombosis risk factors. Key insights on health implications. 🩸🤖
Global trends and hotspots in robotic surgery over the past decade: a bibliometric and visualized analysis.
Robotic surgery has rapidly evolved, with significant research trends identified from 2014 to 2023. 📈🤖
Digital-Tier Strategy Improves Newborn Screening for Glutaric Aciduria Type 1.
A digital-tier strategy significantly reduces false positives in newborn screening for Glutaric Aciduria Type 1. 📉👶
Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as additional parameters.
A recent PubMed article highlights key factors for diagnosing malnutrition in chronic gastrointestinal diseases using machine learning. 🤖🍽️
Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review.
Wearable tech in healthcare needs explainability. 🤖 Our review highlights XAI's role in enhancing data transparency. 📊
Can artificial intelligence improve patient educational material readability? A systematic review and narrative synthesis.
AI can enhance patient education materials' readability, improving health literacy and outcomes. 📚🤖 Review highlights key findings.
GYNs at the REI gates: unsolvable conundrum or unambiguous opportunity?
Exploring the role of GYNs in expanding access to fertility care. 🤝💡 Innovations and collaboration are key!
Vietnam to Establish Its First AI-Driven Virtual Hospital
Vietnam is set to launch its first AI-driven virtual hospital, focusing on preventive healthcare and remote patient care. 🏥🤖
Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma.
A recent study reviewed highlights the random survival forest model's effectiveness in predicting early recurrence of hepatocellular carcinoma post-surgery. 📊🔍