AI knows no bounds. The medical field is an obvious place for AI to be integrated into helpful, time-saving, even disruptive products. Simple AI applications like Augmedix use ambient listening and natural language processing to capture the conversation between patient and doctor then summarize into notes along with the treatment plan. Everything is transferred automagically into the patient's electronic records. This allows the physician to focus solely on the patient rather than typing away on a laptop or tablet. Everyone will welcome AI tools that automate billing, coding, insurance claims, records, etc. The AI doesn't just automate tasks (bing, bang, boom) but it can actually "see" and consider years worth of patient history to better understand what needs to be done for optimal results. Going deep, companies like Butterfly Network, Inc. and Enlitic uses AI to help radiologists become more efficient while reading scans. #aiformedicalpractices
David Schwall’s Post
More Relevant Posts
-
HuatuoGPT-o1 is a new, large language model (LLM) specifically designed for advanced medical reasoning. This innovative AI tool aims to improve medical diagnostics and treatment planning. The episode highlights its potential applications in healthcare. The focus is on its capabilities in complex medical decision-making. Its creation signifies a significant step forward in AI-powered healthcare. https://lnkd.in/dz2g4Bm8
To view or add a comment, sign in
-
-
Spring AI’s latest blog highlights agentic patterns that simplify and enhance Large Language Model (LLM) agents. These patterns drive real-world innovation across industries: 🔬 Life Sciences: Automating clinical trial data analysis using LLM agents for faster regulatory submissions. 🏥 Healthcare: Enhancing AI-driven medical imaging diagnostics, reducing false positives by integrating structured workflows. 🏛 Public Sector: Streamlining public health surveillance with AI-powered agents analyzing vast datasets in real time. Explore more: https://lnkd.in/dNtwjZdC #AI #SpringAI #HealthcareAI #PublicSectorInnovation #LifeSciences #AgenticPatterns
To view or add a comment, sign in
-
In this special BackTable episode, Dr. Aditya Bagrodia sits down with Elie Toubiana, founder and CEO of ScribeMD.ai, to discuss the transformative potential of artificial intelligence (AI) in medical documentation. Their conversation covers the capabilities and benefits of using an AI-driven medical scribe that ensures HIPAA compliance, reduces physician burnout, and enhances patient interactions. Elie also shares his insights about the technology’s adaptability across various medical fields. Finally, Dr. Bagrodia and Elie discuss ethical considerations surrounding applications of AI in other aspects of healthcare, such as medical workup and diagnosis. Listen now: https://lnkd.in/djzkQM-F #MedEd #MedTech #BackTable #Innovation #ArtificialIntelligence #ENT177
To view or add a comment, sign in
-
Full comparison table: Medical AI-Scribes vs Dragon Medical One: Both utilise AI to assist in creating clinical documentation, but there are some key differences in how clinicians use them and how they function. Find the link to the full comparison article in the comments 👇 Any features we have missed? Please leave a comment!
To view or add a comment, sign in
-
-
Full comparison table: Medical AI-Scribes vs Dragon Medical One: Both utilise AI to assist in creating clinical documentation, but there are some key differences in how clinicians use them and how they function. Find the link to the full comparison article in the comments 👇 Any features we have missed? Please leave a comment!
To view or add a comment, sign in
-
-
Full comparison table: Medical AI-Scribes vs Dragon Medical One: Both utilise AI to assist in creating clinical documentation, but there are some key differences in how clinicians use them and how they function. Find the link to the full comparison article in the comments 👇 Any features we have missed? Please leave a comment!
To view or add a comment, sign in
-
-
Full comparison table: Medical AI-Scribes vs Dragon Medical One: Both utilise AI to assist in creating clinical documentation, but there are some key differences in how clinicians use them and how they function. Find the link to the full comparison article in the comments 👇 Any features we have missed? Please leave a comment!
To view or add a comment, sign in
-
-
Have you seen Med-Gemini? While AI, like Google’s Med-Gemini, has shown remarkable advancements in medical tasks, it’s important to note that current regulations prohibit AI from replacing doctors or performing medical duties. However, tools such as Med-Gemini serve as valuable references, enhancing medical professionals’ bedside manner and preventing oversight. Despite its impressive performance in tests, Med-Gemini cannot yet replace human expertise. Nonetheless, its ability to excel in tasks like summarizing medical information and improving the accessibility of complex medical data demonstrates the potential for AI to augment healthcare practices. #health #medical #genai #futureofwork 𝗡𝗼𝘁𝗶𝗰𝗲: The views expressed in this post are my own. The views within any of my posts, or articles are not those of my employer or the employers of any contributing experts. 𝗟𝗶𝗸𝗲 👍 this post? Click 𝘁𝗵𝗲 𝗯𝗲𝗹𝗹 icon 🔔 for more!
To view or add a comment, sign in
-
🚀 𝗔𝗜 𝗣𝗶𝗻𝗽𝗼𝗶𝗻𝘁𝘀 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗘𝗿𝗿𝗼𝗿𝘀 𝗪𝗶𝘁𝗵 𝟳𝟬% 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆: 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗡𝗼𝘁𝗲 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 Key insights from MEDEC’s new research on AI error detection: 📊 Dataset Scope: • 3,848 clinical texts • 50% containing critical errors 🔬 AI vs. Physicians: • 𝟳𝟬% detection accuracy vs. ~𝟴𝟬% for medical doctors • Faster and safer diagnoses, streamlined care 💡 Healthcare Impact: • Fewer adverse events → Reduced costs • Better patient outcomes & operational efficiency 👇 Check out comments section for references 🤔 Question for healthcare leaders: How can you leverage AI to enhance clinical note accuracy? #AIinHealthcare #DigitalHealth #MedicalAI #HealthTechInnovation
To view or add a comment, sign in
-
Full comparison table: Medical AI-Scribes vs Dragon Medical One: Both utilise AI to assist in creating clinical documentation, but there are some key differences in how clinicians use them and how they function. Find the link to the full comparison article in the comments 👇 Any features we have missed? Please leave a comment!
To view or add a comment, sign in
-