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NorthShore University HealthSystems radiologist Dr. Georgia Spear is embodying clinical excellence!👏 Read more about how Dr. Spear is using AI to detect, prevent, and treat breast cancer through the link below.

#AI is being used to spot abnormalities in #mammograms by comparing a mathematical representation of normal mammograms to those with cancer. ☑ This may reduce workloads of radiologists by 30% and increase cancer detection. As a professional in medicine, what do you think? Credits to: The New York Times #HealthcareProfessionals #DoctorsandNurses #HCPConnect #MedTech #WomenInMedicine

🎯7 million mammograms and almost 2 million tomo studies🎯 Trusted users trust #Transpara In multiple head to head evaluations, Transpara has been chosen as the #BreastAI vendor that key opinion leaders around the world choose to support their work. We remain the only Breast AI vendor shown to improve cancer detection while decreasing workload in a randomized controlled trial - the highest level of clinical evidence. 🌐Globally, we've evaluated almost 7 million mammograms, and almost 2 million tomo studies. 🥇And we're proud to be the ONLY Breast AI vendor that improves our algorithm performance every year. Why are you waiting? See why users trust Transpara to give them Workflow, Confidence, and Results. #TransparaWorkflow #TransparaConfidence #TransparaResults

Yesterday, on World Health Day, millions across Europe faced the harsh reality of metastatic cancer, grappling with the threat of fractures and diminished quality of life. But amidst these challenges, there's hope. ⚕ Introducing #METASTRA, a pioneering initiative set to revolutionise metastatic cancer care. Through cutting-edge biomechanical computational models driven by AI and Physiology, METASTRA offers clinicians unprecedented insights into fracture risks associated with spinal metastases. Learn more about our project 👉 https://lnkd.in/dN5Kmw5q #WorldHealthDay #MetastaticCancerCare #HealthcareInnovation

MIT's SAIL and Massachusetts General Hospital have created Mirai, an Al model that detects breast cancer risk up to five years early using mammograms. Mirai outperforms the Tyrer-Cuzick model and other Al methods, boasting a C-index of 0.76 for better accuracy, sensitivity, and specificity. It works well across different races, ages, and breast densities, making it a reliable tool for identifying high-risk patients. This breakthrough highlights Al's growing role in healthcare. Do you think models like Mirai will soon be a standard part of medical care? #AI

"Synthetic Soldiers" 🤔 | Turning #Tcells into #Immortal Warriors 👍 | Terrific OPEN ACCESS 'Insight' Article Now at Rockefeller University Press Journal of Experimental #Medicine 👏 | #immunotherapy | #cancer | #tumours | The creation of synthetic T cell states has captivated the field of cell-based therapies. Wang et al** describe how disruption of BCOR and ZC3H12A unleashes anti-tumor T cells with unprecedented lifespan and killer instinct. Here*, Nicholas Restifo, MD & Luca Gattinoni ask whether we are witnessing the birth of immortal super-soldiers in medicine? *https://lnkd.in/ejnMcFwz **https://lnkd.in/e9RFiQs3 Celentyx Ltd #immunooncology www.celentyx.com Professor Nicholas Barnes PhD, FBPhS Omar Qureshi Catherine Brady FIGURE | Left: Hallmarks of anti-tumor efficacy in adoptively transferred T cells. This figure delineates six interrelated hallmarks that underpin the anti-tumor efficacy of adoptively transferred T cells | Right: Functional attributes of physiological and synthetic T cell states. This figure illustrates the distinct phenotypic and functional characteristics of three specialized T cell states. Plus signs indicate robustness of the designated function, minus signs indicate the absence of the function |

Notable advancements in diagnostics, such as Comprehensive genomic profiling, Digital Pathology, and Artificial Intelligence (AI), have significantly enhanced precision in cancer care. This transformative progress ensures not only prompt treatment but also expedites the recovery process. Embracing these innovative technologies marks a pivotal moment in the pursuit of refined healthcare solutions. This #WorldCancerDay, let’s educate ourselves and those around us about the developed ecosystem for cancer care because only together we can #ConquerCancer. To learn more about cancer and cancer prevention, visit: https://lnkd.in/dK7JVqFr #Roche | #HealthWithDiagnostics | #CancerAwareness | #ClosingTheCareGap

Catch up: The AI Revolution in Cancer Imaging Watch more: https://gres.hm/ai-cancer Dr Richard Sidebottom* demystifies the AI technological revolution; one of the most disruptive technologies of all time, promising safer, faster and more accurate healthcare. *of The Royal Marsden NHS Foundation Trust ❕You can still register to watch the next lecture in this series, Immunotherapy: Cure for Metastatic Cancers? by Prof James Larkin at: https://lnkd.in/e2udQ86N #medicine #computerscience #AI #biotechnology #freelearning

While the potential of extracellular vesicles in cancer diagnostics and prognostics is an unquestionable fact by now, there are still challenges to overcome. One such challenge is the fact that even though cancerous EVs are quite distinguishable from healthy ones, they all exist in the same body fluid. Since cancerous EVs are even much more scarce compared to the healthy ones, especially in the early stages of the disease, they are difficult to detect, posing a difficulty on early diagnosis. As part of the efforts to overcome this challenge, one possible way is set by laser tweezers, trapping EVs one-by-one for single EV analysis. In one such study, a group of researchers from Canada used a double nanohole optical tweezer to distinguish non-malignant, non-invasive cancerous, and invasive cancerous cell-line EVs. By integrating 1D convolutional neural network-based AI algorithm into their work, the researchers managed to differentiate MCF10A, MCF7, and MDA-MB-231 EVs with better performance than the state-of-the-art. Even though there seems to be still room (and necessity) for improvement for clinical-level sufficiency in terms of performance, I must say that the approach is really impressive and promising. If you are interested in further reading: https://lnkd.in/gEZ6cgR5 #exosomes #extracellularvesicles #singleEVcharacterization #opticaltrapping #opticaltweezers #cancerdiagnosis #cancerprognosis

🌟Never miss this interesting #Article 🔥Article Views 2186; Citations 7 Title: Phenomapping of Patients with Primary Breast Cancer Using Machine Learning-Based Unsupervised Cluster Analysis 👥Sara Ferro et al. 🏥Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova 🔗https://lnkd.in/gnZRT_kt Journal of Personalized Medicine MDPI Figure. Meila’s variation of information (VI) of similarity for the two clusters obtained with four algorithms. (a) Meila’s VI for K-means; (b) Meila’s VI for SOM; (c) Meila’s VI for HAC; (d) Meila’s VI for the GMM.