HEALTHCARE SIMULATION MIDDLE EAST’s Post

This is an excellent peer-reviewed article about using simulation to teach research. "Simulation creates a safe learning environment that allows testing new clinical processes and enhancing individual and team skills before encountering actual patients." Yes! As someone who learns well through simulated situations, I hope we continue to explore and implement this exciting teaching method. #ACRP #ClinicalResearchLearning

SCOPE - Summit for Clinical Ops Executives The leading conference for Clinical Ops Executives is taking place next week in Orlando. I want to invite those at the conference to attend a presentation by our Founder, David Hadden. Learn about the impact of simulation on a complex global Phase 3 study. #Pro-ficiency #simulation #SCOPE #clinicaltrials

At D3H-Group, we're exploring alternative formats of the diagnostic processes in the field of medicine through a data-driven, evidence-based approach to increase the reliability of the diagnosis. As founders of a pioneering startup specializing in the digital diagnosis of Cardiovascular Disease (CVD), we're merging the best of engineering innovation with medical expertise to enhance precision and reliability in diagnosis. In the world of engineering, presenting an issue without diagrams or figures might seem unusual, yet in the medical domain, it's common to rely on opinion-based diagnosis. Our mission is to bridge this gap by infusing engineering rigor into medical diagnostics, ensuring a comprehensive and evidence-backed assessment every time. 🔬 By leveraging an evidence-based approach, we aim to enhance not just accuracy, but also the understanding of complex physiological processes. Take, for instance, the cardiac cycle and the combustion engine cycle. While these may seem worlds apart, they share a fundamental similarity in their scientific underpinnings. Our approach acknowledges these parallels while embracing the nuances that make medical diagnostics unique. Join us on this exhilarating journey as we redefine the future of diagnosis, one evidence at a time. #HealthTech #Innovation #EvidenceBasedMedicine #StartupLife #D3HGroup #CVD #CardioDiseases #DigitalHeartHealthHub

The next generation just hits different. They learn in different ways and faster than previous generations. A lot of them are growing up on virtual reality and will be moving into augmented reality. With the help of NVRT Labs we can meet them where they are…in a digital space from the comfort of…wherever they are.

Day 1 HRS - https://heartrhythm.com A predicted 16 million Americans will be afflicted by Afib in the coming years, as such, researchers and engineers are working to improve patient outcomes in the electrophysiology space. With the recent commercial emergence of Pulse Field Ablation or PFA, patients are being treated with electrical pulses to induce cardiac cell death. In the years leading up to the commercial emergence of PFA, ATL Technology has been working with OEM’s to develop PFA devices that are now benefiting patients. As you develop new technologies, look for a partner who has historical experience in developing technologies, such as ATL.

Next OPEN ACCESS #ClinicalSimulation Webinar (Feb 28th, 10AM PST, UTC-8) "From Page to Stage: Using SimVS to Build a Clinical Simulation Scenario" - https://lnkd.in/eQXn5ASR

Next OPEN ACCESS #ClinicalSimulation Webinar (Feb 28th, 10AM PST, UTC-8) "From Page to Stage: Using SimVS to Build a Clinical Simulation Scenario" - https://lnkd.in/eQXn5ASR

🎉 Exciting News! 🎉 I am thrilled to share that I have successfully completed my HCI project, "𝑬𝑪𝑮 𝑷𝒆𝒓𝒔𝒐𝒏𝒂𝒍 𝑰𝒏𝒇𝒐 𝑳𝒐𝒄𝒌", which involved an in-depth exploration and handling of ECG signals. This journey included: 🧬𝐏𝐫𝐞𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: Cleaning and preparing the ECG data for analysis. 🔍𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐱𝐭𝐫𝐚𝐜𝐭𝐢𝐨𝐧: Identifying critical features from the ECG signals to ensure accurate analysis. 🤖𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Implementing advanced algorithms to process the data and provide meaningful insights. The end result is a sophisticated system capable of matching ECG inputs with verified records in the database, delivering personalized information based on this biometric verification. This project has been an incredible learning experience, bridging the gap between human-computer interaction and advanced biomedical signal processing. I am eager to see how these insights can be applied to real-world healthcare solutions. You can check it from this repo: https://lnkd.in/ecwVqRZh #HCI #MachineLearning #ECG #BiomedicalEngineering #TechInnovation #DigitalSignalProcessing

𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐌𝐚𝐫𝐤𝐞𝐭 𝐰𝐨𝐫𝐭𝐡 $𝟒.𝟔 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 𝐛𝐲 𝟐𝟎𝟐𝟖 ➡𝑫𝒐𝒘𝒏𝒍𝒐𝒂𝒅 𝑷𝑫𝑭 𝑩𝒓𝒐𝒄𝒉𝒖𝒓𝒆: bit.ly/3SdCP6h  The North American healthcare simulation market is expected to be worth USD 4.6 billion by 2028. growing at a CAGR of 15.7% during the forecast period. 𝐓𝐡𝐞 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐟𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐢𝐧 𝐭𝐡𝐢𝐬 𝐫𝐞𝐩𝐨𝐫𝐭 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: CAE Canada, Laerdal Medical, Simulab Corporation, Simulaids Ltd, Limbs & Things, Kyoto Kagaku America Inc., Mentice 𝐓𝐡𝐞 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐭𝐡𝐚𝐭 𝐚𝐫𝐞 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐢𝐧 𝐭𝐡𝐢𝐬 𝐦𝐚𝐫𝐤𝐞𝐭 𝐠𝐥𝐨𝐛𝐚𝐥𝐥𝐲: Healthcare Human Factors   Society for Simulation in Healthcare (SSH)   Elevate Healthcare      Avidex in Healthcare      Leader Healthcare      HealthStream      Evidera      Air Methods      Downstate Health Sciences University     D'Youville University      Congress of Neurological Surgeons (CNS)     BigBear.ai     Gaumard Scientific      Paragon One      Oxford Medical Simulation ReliSource      SandboxAQ      RxDataScience        Schlesinger Group       Robosoft Technologies      NetSPI      West Coast University Canfield Scientific   #HealthcareSimulation #MedicalSimulation #SimTech #MedEd #SimulationTraining #HealthTech #Simulators #MedSimulation #PatientSafety #ClinicalTraining   

Unlocking the Power of MABs with Statistical Inference! Are you leveraging Multi-Armed Bandit (MAB) algorithms for A/B testing or decision-making in e-commerce, healthcare, or policymaking? Recent advancements incorporate delayed feedback, a common challenge! But traditional MAB literature often lacks strong statistical inference for learned policies. Here's the exciting news! Lei Shi et.al. research proposes a unified framework for policy evaluation with delayed feedback, allowing for a target policy different from the data collecting one. This means: Improved decision-making: Quantify the uncertainty of your MAB policies for better confidence. Adaptability: Handles delays associated with different treatment arms. Robustness: Doesn't rely on perfect knowledge of the delay mechanism. Want to learn more? Challenges you face with MABs? Let's connect in the comments and discuss how we can help! #MAB #reinforcementlearning #ecommerce #healthcare #policymaking #statistics #research Encourage comments by asking about challenges users face with MABs. Offer to connect and discuss how your research can help. https://lnkd.in/g2aaaA2i