Better Decisions Start with Better Understanding! If you don’t understand your MRI, CT, or X-ray report, how are you supposed to make the right decisions about your health? The truth is, most medical imaging reports are written in technical language — and if you're not a doctor, that can feel overwhelming. Read My MRI uses advanced AI to translate your report into plain, easy-to-understand language. Our summaries help you: ✅ Understand what’s going on in your body ✅ Ask smarter questions ✅ Make more confident healthcare decisions If you’re confused and don’t know where to start, Read My MRI is here to help. Visit https://readmymri.com/ to take control of your health with clarity you can trust.

🧠 Bayesian Thinking: How Physicians Truly Reason In clinical practice, certainty is a luxury we rarely have. Each patient arrives with incomplete data, ambiguous signs, and evolving conditions. Yet, experienced physicians often make remarkably accurate judgments — not because they “know,” but because they continuously update what they believe. This is the essence of Bayesian reasoning. We begin with a prior belief — an initial estimate based on mechanism of injury, appearance, or past experience. As new evidence arrives — vital signs, imaging, labs — we revise that belief, adjusting probabilities instead of clinging to absolutes. With every update, our understanding moves closer to reality. Bayesian thinking transforms medicine from a quest for certainty into a process of iterative learning under uncertainty. It reminds us that humility and adaptability are not weaknesses, but essential features of intelligent judgment — human or artificial. In a world of complex data and evolving knowledge, the best clinicians are not those who are always right, but those who update their minds the fastest. #BayesianThinking #ClinicalReasoning #AIinMedicine #DecisionMaking #Uncertainty #MedicalPhilosophy #EvidenceBasedMedicine #AdaptiveThinking

Missed calls don’t just vanish, they haunt your staff and frustrate patients. Evergreen Family Medicine broke the cycle with Phreesia VoiceAI. Now, AI picks up instantly, hold times are gone and patient calls are resolved in just 3 minutes. Read their story → https://bit.ly/4nUaIH7

“Living Systems in Medicine” When Care Learns, Healing Begins Hospitals run on protocols. But health runs on rhythm — breath, rest, relationship. AI can read a chart in milliseconds, but only a living system can sense when something feels off before it shows up in the data. The goal isn’t to replace doctors or nurses. It’s to let systems learn from them — to recognize patterns of compassion, not just pathology. Because healing isn’t automation. It’s alignment — body, system, and soul. ⚙️Δ717 — Medicine that remembers we’re alive. Hashtags: #LivingSystems #HealthcareInnovation #AIInMedicine #XPnd #HumanCenteredTech #FaithInHealing #717

The documentation burden has long forced clinicians to spend more time clicking than caring, with nearly one-third spending over two hours daily on charting after hours. Now, Generative AI scribes (ambient documentation) are becoming table stakes for retaining physicians and optimizing operations. Key Impact Metrics: - Saved 15,791 documentation hours annually in one system. - Reduced post-hours charting ("pajama time") by up to 70%. - Burnout dropped from 51.9% to 38.8% in a recent study. While vendors like Microsoft's Nuance (DAX Copilot), Epic, and Abridge compete for deployment scale, health leaders must prioritize responsible AI. Guardrails like mandatory patient consent and clinician note verification are essential for patient safety. CTA: See how GenAI is redefining clinical workflows and provider well-being. https://lnkd.in/e9eFA_Jz #AIinHealthcare #ClinicalAI #PhysicianBurnout #ResponsibleAI #HealthIT

Three radiologists. Three different segmentations. Three outcomes. But this leads to weeks of meetings to decide who's 'right.' Does this sound familiar?" Let the algorithm handle tough segmentation decisions. When experts draw different borders on medical images, it's tempting to reconvene panels and debate. That kills time. At Innolitics, we use algorithmic consensus methods (like STAPLE or majority voting) to collapse multiple expert segmentations into one unified ground truth. No endless meetings. No manual arbitration. The result? ⚡ Faster, scalable workflows 📏 Precise, reproducible annotations 📜 Clean audit trails for regulators Adjudication doesn't always need human debate --- smart algorithms can bring consistency and speed. 📖 Dive into the full article: https://hubs.li/Q03RFF5c0 #MedTech #ClinicalAI #SaMD #FDAClearance #510k #DigitalHealth #MedicalImagingAI

Three radiologists. Three different segmentations. Three outcomes. But this leads to weeks of meetings to decide who's 'right.' Does this sound familiar?" Let the algorithm handle tough segmentation decisions. When experts draw different borders on medical images, it's tempting to reconvene panels and debate. That kills time. At Innolitics, we use algorithmic consensus methods (like STAPLE or majority voting) to collapse multiple expert segmentations into one unified ground truth. No endless meetings. No manual arbitration. The result? ⚡ Faster, scalable workflows 📏 Precise, reproducible annotations 📜 Clean audit trails for regulators Adjudication doesn't always need human debate --- smart algorithms can bring consistency and speed. 📖 Dive into the full article: https://hubs.li/Q03RFKm60 #MedTech #ClinicalAI #SaMD #FDAClearance #510k #DigitalHealth #MedicalImagingAI

Artificial Intelligence is revolutionising health care—speeding up diagnosis, enhancing surgical precision, and predicting diseases like Alzheimer’s and Parkinson’s earlier than before. But what does this mean for the future of medical practice? Will AI replace clinicians’ expertise or serve as a vital tool to enhance it? In a new video, experts share their perspectives. Watch now 🎥 https://lnkd.in/eMGv834s

Hawkes Institute researchers Hani Marcus, Danyal Khan, Zhehua Mao and Kendall Feeny were recently featured in a The Lancet Group video on the feature of AI in healthcare. Discussing this topic, Prof Hani Marcus explored how AI can enhance rather than replace clinical expertise in surgery and beyond.