Industry Insights on Healthcare AI

Learn more about the Dec. 31, 2024 deadline for B.11 compliance and the two paths EHR vendors can take to meet ONC requirements.

Discover how the ONC's HTI-1 rule ensures the safe, transparent, and effective use of AI-driven Decision Support Interventions in healthcare.

Explore the transformative potential of generative AI in healthcare, its current use by patients and providers, and the need for equitable access and responsible implementation to ensure widespread benefits.

Examine a study that explores how doctors view AI in healthcare, finding a mix of awareness and cautious optimism about its potential to improve diagnoses, manage chronic conditions, and streamline healthcare.

Explore a physician's innovative approach to familiarization with generative AI in their personal life, aiming to enhance its future application within a clinical setting.

This article offers researchers a step-by-step guide on transforming complex scientific data into user-friendly, interactive applications using Streamlit for enhanced accessibility and clinical utility.

Learn about the lack of open-source success stories for rare diseases due to limited resources, fragmented research, and low awareness, and how a centralized platform, funding, awareness, and data security can bridge this gap.

Explore five key trends in healthcare AI for 2023, highlighting how machine learning is revolutionizing personalized medicine, predictive analytics, clinical decision support, drug development, and population health management.

Discover how generative AI is used by doctors for research, writing, and improving patient care efficiency, while acknowledging limitations like factual inaccuracies and the irreplaceable role of human expertise.

This checklist offers a structured approach to integrating Decision Support Interventions in healthcare systems. It ensures responsible implementation, compliance with ONC regulations, and ultimately, maximized patient benefits.

Health Universe launches a platform for researchers to share machine learning models, aiming to improve patient care through collaboration and easier access for healthcare professionals.