Cogstate’s Post

🎉Exciting news🎉 Dear Linkedin Network, I am thrilled to share with you our end-of-year project titled "Web Application for Early Detection of Alzheimer's Disease through Deep Learning from Structural Brain MRIs".🧠💻 This project has been an incredible journey, full of learning and technical challenges. A huge thank you to our supervisor, Ms. Sonia Ben Hassen, for her unwavering support, valuable advice, and expertise throughout this project. Her guidance has been crucial to achieving our goals and the success of our work. 🔍 We have developed an innovative web application to help doctors diagnose Alzheimer's disease earlier. This application is based on a deep learning model trained on structural brain MRI images, capable of detecting early signs of the disease, even before the onset of clinical symptoms. 👩⚕️Doctors can simply upload a patient's MRI image into the application, which will then provide an accurate classification of the disease stage. This allows for early diagnosis, essential for tailored patient management of those with mild cognitive impairment. 💡Our project aims to improve the screening of Alzheimer's disease and facilitate patient monitoring in the early stages of the disease. The developed web application will be a valuable tool for doctors in their clinical practice. We are proud of the work accomplished and look forward to continuing to contribute to research and innovation in the field of healthcare. #DeepLearning #Alzheimer #MRI #WebApplication #Innovation

🚀 Groundbreaking Study on Early Dementia Detection 🚀 In a transformative stride within the medical community, researchers have harnessed the power of machine learning to analyze blood proteins, unveiling a promising avenue for early dementia diagnosis. 🧬 Published in Nature Aging, the study delved into 1,500 blood proteins from over 50,000 UK Biobank participants, identifying four key proteins - GFAP, NEFL, GDF15, and LTBP2 - as significant predictors of future dementia in healthy adults. This marks a monumental leap towards non-invasive blood tests for Alzheimer’s and other dementias, potentially catching the disease before symptoms arise. 💡 The implications are vast and hopeful: early detection could lead to interventions that delay or even prevent the onset of dementia, reshaping treatment paradigms and offering a beacon of hope for millions. 🌟 As we stand on the brink of this medical revolution, it's a reminder of the profound impact that data science and AI continue to have on our lives, far beyond the tech world, touching the very core of human health and well-being. 🌍 #DementiaResearch #MachineLearning #MedicalInnovation #DataScience #EarlyDetection #HealthcareRevolution

🔬 Pioneering the Future of Alzheimer's Diagnosis with NeuroCogniAI 🧠 At NeuroCogniAI, we are committed to revolutionizing the way we approach the early and accurate diagnosis of Alzheimer’s disease. Our advanced diagnostic tool harnesses the power of AI and computer vision to provide healthcare professionals with cutting-edge insights, facilitating earlier intervention and better patient outcomes. The early detection of Alzheimer's is critical, and NeuroCogniAI is dedicated to supporting clinicians with a reliable, user-friendly platform that integrates seamlessly into existing workflows. Together, we aim to enhance diagnosis accuracy and improve the quality of life for millions affected by this condition. Stay tuned as we continue to innovate and collaborate with the brightest minds in health tech to bring meaningful solutions to the forefront of dementia care. #AlzheimersAwareness #NeuroCogniAI #HealthcareInnovation #AIinHealthcare #EarlyDiagnosis #DementiaCare #HealthTech #ArtificialIntelligence

Q&A with Dr. Carl Marci on OM1’s New Alzheimer’s Disease Dataset The future of Alzheimer’s disease detection and treatment may lie in AI-based datasets encompassing an abundance of real-world evidence from a large number of patients. Healio spoke to Carl D. Marci, M.D., Chief Clinical Officer at OM1, Inc., to gain his insights into how our company’s new dataset can move the process forward. Key Takeaways; 🧠A large, real-world dataset allows clinicians to track early warning signs of Alzheimer's disease. 🧠The dataset leverages medical claims, EHRs, and lab and imaging data to foster health care collaboration Detecting Alzheimer's early is challenging. The signs are subtle, and each individual is unique. But OM1's Alzheimer’s Disease Dataset, when combined with our advanced AI and machine learning platform, OM1 PhenOM®, allows us to create a new roadmap for early detection. The goal is to shift the timeline from reacting to symptoms to preventing them from progressing in the first place. Interested in learning more? Check out the following links; 📍Read, “Q&A: New Alzheimer’s dataset allows ‘whispers from the brain’ to assist in early detection,” here; https://lnkd.in/eQyJZQhb 📍Book a meeting with us; https://lnkd.in/eJcKBAJK #alzheimersdisease #rwd #AI #patientjourneys #Healio

"Early Diagnosis, Longer Memories: Fighting Alzheimer's." Excited to share that I presented our research paper at the 15th International Conference on Computing, Communication, and Networking Technologies (ICCCNT) held at IIT Mandi from June 24th to 28th, 2024. 📄Paper Title: "Alzheimer's Disease Detection Through Spatially Attentive Enhanced Low-Mid-High Level Feature Modelling using Deep CNN." Our proposed model detects Alzheimer's based on MRI images of the brain. We used Atrous CNN and Spatial Attention Mechanism to detect low, mid, and high-level features. Unlike previous works, our approach emphasizes low and mid-level features, which were often neglected. Our proposed model achieved an accuracy of 94.8%. 🧠 Importance of Alzheimer's Detection: According to WHO, currently more than 55 million people have dementia worldwide, with over 60% living in low-and middle-income countries. Every year, there are nearly 10 million new cases. Early detection plays a crucial role in slowing its progression. #Research #Alzheimers #DeepLearning #CNN #ICCCNT2024 #HealthcareInnovation #MachineLearning #IITMandi #ICCCNT

The paper by Negin Ashrafi, Armin Abdollahi, and Maryam Pishgar discusses the enhancement of predictive models for ventilator-associated pneumonia (VAP) in traumatic brain injury (TBI) patients using advanced machine learning techniques. They implemented six different models and found that "XGBoost" significantly outperformed others, with an AUC of 0.940 and an accuracy of 0.875, marking a 23% improvement over previous studies. This research underscores the potential of refined feature selection and ensemble learning techniques in improving early VAP detection, which is crucial for better patient outcomes and resource management in healthcare. #MachineLearning #Healthcare #TraumaticBrainInjury #VAP #PredictiveModeling #AIinMedicine #Research

This Parkinson's Awareness Month, we're excited to share how AI is transforming Parkinson's care. In my latest article for WRAL TechWire, I discuss how Parkinson's is the fastest-growing neurological disorder in the world, and may be growing due to man-made environmental toxicity. AI and digital health innovators are stepping in to help, with innovative tools from MIT labs, Charco Neurotech, CareYaya and Eurofarma. From detecting Parkinson's from breathing patterns to vibration therapy to reduce tremors... read about what's being done to provide critical support for patients and caregivers. But, we must do more. It's time to invest in groundbreaking solutions and provide robust support for the Parkinson's community. Together, we can pioneer a new era of empowerment and hope for patients and families everywhere. ❤️ 🌟 h/t Nicole Pozzo

AI in dementia support 8 Isn’t there anything to detect mild cognitive impairment likely converting to Alzheimer’s disease (AD) as early as possible? Now that Lecanemab (LEQEMBI as the brand name), which is a new promising drug for preventing progression to AD, came up recently, it has become a significant clinical request. Lecanemab is currently applied only to mild cognitive impairment due to AD and early AD dementia. BrainSee software powered by artificial intelligence (AI) allows us to predict progression to Alzheimer’s disease in 5 years using MRI images and cognitive tests.   I could not reach the details of the AI, taking a glance at the official site. However, it could give hope to the patients because the AI may become an alternative option to expensive PET exams. BrainSee was just approved by the Food and Drug Administration (FDA) in January 2024. https://brainsee.ai #dementia #ai #alzheimer #brainsee #lecanemab

NICE Endorses Brainomix AI-Enabled Software in Stroke 🧠🤖 The UK health assessor the National Institute of Health and Care Excellence (NICE) has endorsed the use of Brainomix 360 (formerly known as e-Stroke) to help clinical decision making in stroke. The artificial intelligence (AI)-powered tool from Oxford-based Brainomix was one of only two products to obtain this select endorsement amongst more than a dozen technologies that were assessed by NICE. The NICE guidance elevates the Brainomix 360 stroke platform, the European market leading solution now entering the US market, to an evidence generation framework, which enables stroke units across the UK to utilize the technology while further evidence is collected. More than 100,000 strokes occur every year in the UK, making it is a leading cause of disability and one of the most common causes of early death. The Health Technology Assessment (HTA) acknowledged that there is evidence showing that... Continue reading... https://lnkd.in/dY-vNe5F #healthtech #health #AI #technology #innovation #businessnews #businessintelligence