Niyaz Wani’s Post

🚀 Hello Connection My Latest Research on Brain Tumor Detection! 🧠🔬 Brain tumor detection is a critical field where early diagnosis can significantly improve patient outcomes. My research focuses on leveraging advanced technologies (such as [mention any specific technology like AI, MRI analysis, etc.]) to enhance the accuracy and efficiency of detecting brain tumors. In our work, we aim to develop innovative methods that can help medical professionals identify tumors at an early stage, ultimately saving lives and improving quality of care. I’m proud to announce that our research paper has been published! 📄 You can read it here : https://lnkd.in/degHeRdb #BrainTumorDetection #IJSREM #ResearchPaper #PublishedResearch

mlangles's Predictive AI unlocks the highest degree of accuracy in detecting and classifying brain tumors!    mlangles identifies and classifies brain tumors achieving 99% accuracy, resulting in more precise and prompt treatment. Connect with us to learn more about how mlangles elevates the Predictive AI game for brain tumor classification and advances healthcare! Visit our website @ mlangles.ai #mlangles #AI #innovation #healthcare #braintumor #cancerawareness

How Doctors Could Soon Use AI to Detect Brain Cancer : #aiinhealthcareresearch - Recent advancements in artificial intelligence (AI) have significantly enhanced the detection of brain tumors, offering accuracy levels comparable to human radiologists. A notable study published in Biology Methods and Protocols by Oxford University Press demonstrates that AI models can effectively distinguish between cancerous and healthy brain tissue in MRI scans. Using innovative techniques like transfer learning from camouflage detection, these AI systems can identify cancerous tissues with high precision while offering explainable insights to foster trust among medical professionals. MEDPULSE AI Read More ▶️ https://buff.ly/3B20PUI 💡 #aibraincancer #aicancerdetection #MedPulseAI #AIinHealthcare #AIinMedicine

Reconstructing 2D ultrasound images into 3D volumes offers significant advantages, from quantitative measurements to enhanced 3D visualization and interventional guidance. Trackerless 3D freehand ultrasound reconstruction further enhances diagnostic capabilities by providing 3D imaging without the need for external tracking systems, making it more accessible and easier to use in clinical settings. Our latest literature review dives deep into these advancements, the challenges, and potential solutions. Read more here: https://lnkd.in/eScQP3br The Netherlands Cancer Institute #POCUS #Ultrasound #MedicalImaging #HealthcareTechnology #AIinMedicine #3DReconstruction #FreehandUltrasound #Trackerless #3DViulizatin #MedicalDevices #ClinicalInnovation #deeplearning #ai

#ASNR2024 Are you keeping up with the latest in AI-driven for brain tumor segmentation? Join us and Dr. Charles Mellerio at the ASNR’s Industry Collaborative Session on "AI Applications in Brain Tumor Segmentation" and hear directly from neuroradiology experts and industry innovators on clinically translating AI advances to automate tumor volumetrics. Learn more about our tool and participate in a panel discussion. We hope to see you there as we discuss powering clinical decision-making with transformative segmentation technologies. 📆 2:55 pm Tuesday, May 21 📍 Emperors I - Caesars Palace - Las Vegas #AI #braintumor #medicalimaging Lauren G. Eloïse ZANETTI

🌟 Revolutionizing Nasopharyngeal Carcinoma Treatment with Advanced Imaging Techniques! 🌟 A groundbreaking study introduces a novel approach to accurately segment the gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) using non-contrast planning CT scans. This innovative method leverages 3D Semantic Asymmetry Tumor Segmentation (SATs) to enhance the precision of radiation therapy planning. 🔍 Key Highlights: - Traditional methods often rely on MRI scans for tumor delineation, which can lead to registration errors and inaccuracies in treatment planning. - The SATs method utilizes a Siamese contrastive learning framework that capitalizes on the inherent symmetry of healthy nasopharyngeal regions, effectively distinguishing tumors from surrounding tissues. - Extensive experiments demonstrate that SATs outperforms existing state-of-the-art methods, achieving at least a 2% improvement in Dice score and 12% reduction in average distance error. 💡 This advancement not only streamlines the segmentation process but also has significant implications for improving patient outcomes through more accurate radiation dose delivery. 🔗 Explore how this innovative approach can transform NPC treatment protocols and enhance clinical practices! #AI #AIinHealthcare #Algorithms #ArtificialIntelligence #DL #DS #DataScience #DeepLearning #ML #MachineLearning #MedicalImaging #NasopharyngealCarcinoma #RadiationTherapy #Tech #Technology #TumorSegmentation Source: https://lnkd.in/eGeRkEd9

Researchers from the University of Naples and the University of Molise have developed a breakthrough deep-learning model capable of predicting cancer aggressiveness from routine pathology slides. This innovative approach uses AI to predict Ki-67 staining from standard H&E-stained images, eliminating the need for additional staining procedures. The model has shown promising accuracy and could significantly reduce lab workloads, speed up diagnosis, and cut costs. This pioneering work is a major step towards the digitization and automation of pathology, enhancing clinical decision-making and patient care. #digitalpathology #pathologynews Follow the link below to read the article in full... https://lnkd.in/ebtajcw6

AI Advancement in Urology Medical Care. The impact of #AI in detecting prostate cancer is significant and continues to evolve. AI technologies, such as machine learning algorithms, have shown promise in analyzing medical imaging data (such as MRI or ultrasound images) to assist radiologists and clinicians in identifying potential signs of prostate cancer at an early stage. #AugmentedIntelligence refers to the collaboration between human healthcare professionals and advanced technology like #AI. In the context of medicine, Augmented Intelligence can enhance decision-making processes by providing insights from vast amounts of patient data that may not be readily apparent through traditional methods alone. Harvey Castro, MD, MBA. discussion likely emphasizes how these advancements can lead to more accurate diagnoses, personalized treatment plans, improved patient outcomes, and overall efficiency within healthcare systems. Additionally, he might explore the ethical considerations surrounding the use of AI in medicine while highlighting its potential for transforming various aspects of clinical practice. https://lnkd.in/eqzxytCN

Al's ability to revolutionize medical image analysis and enhance diagnostic accuracy marks a new era of possibilities in radiology. #MedicalAdvancements #FutureOfMedicine #ArtificialIntelligence #HealthcareTransformation #ImprovingPatientCare #MedicalAI #CTScans #MRI #DeepLearning #MachineLearning

AI Advancement in Urology Medical Care. The impact of #AI in detecting prostate cancer is significant and continues to evolve. AI technologies, such as machine learning algorithms, have shown promise in analyzing medical imaging data (such as MRI or ultrasound images) to assist radiologists and clinicians in identifying potential signs of prostate cancer at an early stage. #AugmentedIntelligence refers to the collaboration between human healthcare professionals and advanced technology like #AI. In the context of medicine, Augmented Intelligence can enhance decision-making processes by providing insights from vast amounts of patient data that may not be readily apparent through traditional methods alone. Harvey Castro, MD, MBA. discussion likely emphasizes how these advancements can lead to more accurate diagnoses, personalized treatment plans, improved patient outcomes, and overall efficiency within healthcare systems. Additionally, he might explore the ethical considerations surrounding the use of AI in medicine while highlighting its potential for transforming various aspects of clinical practice. https://lnkd.in/eqzxytCN