OSF Innovation’s Post

🚨 We developed a deep learning decision making tool for the identification of #seminoma subtypes using histopathological slides. It is finally out in Clinical Pathology journal Sage https://lnkd.in/gmvQWBUr #deeplearning #cancer #testicularcancer #ai #bioinformatics

Traditional approaches to predicting patient outcomes from histopathology mimic the work of a pathologist. They take features that pathologists already use to stratify patients and create algorithms to automate extracting these characteristics. One major advantage of this approach is interpretability - pathologists already understand what these features look like and so it makes sense when an automated method also demonstrates that cellular diversity is associated with lower survival rates for non-small cell lung cancer, for example. If pathologists already had a superior ability to predict patient outcomes from histopathology, this approach would be great. However, the visual complexity of these gigapixel whole slide images presents a challenge because of the size of the images, their intricate appearance, and the heterogeneity within each. Read this article that I wrote for The Pathologist to learn how advances in AI applying deep learning to digital pathology images can stratify patients by risk. https://ed.gr/eabij #Pathology #CancerResearch #PrecisionMedicine #MedicalImaging #MachineLearning #DeepLearning #ComputerVision

Exciting news from the NHS trial: AI surpasses doctors in spotting early signs of breast cancer! The AI tool 'Mia' analyzed over 10,000 mammograms, detecting cancer in 11 individuals missed by human radiologists. This breakthrough prompts a reevaluation of AI's role in diagnostic radiology, highlighting both its transformative potential and ethical considerations. Mia not only improves diagnostic accuracy but also enhances operational efficiency by reducing wait times. Let's discuss the integration challenges and opportunities AI presents in healthcare to ensure equitable, ethical, and patient-centered care. #AI #Healthcare #BreastCancer #MedicalDiagnostics #Ethics #OperationalEfficiency #NHS_trial

It is quite important not only to develop and implement AI tech into clinical processes. It’s crucial to measure actual effects. Our solution “Clinical decision support system for pathologist in colorectal cancer” based on AI/computer vision showed 25% increase in speed of work of pathologists and increased their sensitivity in finding metastasis in lymph nodes - one of the necessary routine procedures to diagnose stage of cancer. The next step is to measure economic effect based on these findings. That’s what I presented at Russian Diagnostic Summit 2024. We welcome AI researchers and pathologists who are keen to research economic effects of AI in pathology. Join us in crafting the future of AI in healthcare. #digitalpathology #cancer #histology #pathology #ai #rds #russiandiagnosticsummit

Check out this timely article from Health Imaging summarizing a recent study on multi-parametric MRI for prostate cancer screening. The study suggests that machine learning techniques can decrease costs and increase access to high-quality memory and fusion biopsy outside the academic and subspecialty clinical setting. This could ultimately improve care equity. The full article can be found here: https://lnkd.in/ebYgSUiw. #aiinhealthcare #medicine #innovation

Automatic Joint Teeth Segmentation in Panoramic Dental Images using Mask Recurrent Convolutional Neural Networks with Residual Feature Extraction: Can it be useful in Oral Cancer Diagnosis and Management https://lnkd.in/ej6BdgUc

𝗡𝗲𝘄 𝗔𝗜 𝗧𝗼𝗼𝗹𝘀 𝗳𝗼𝗿 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗣𝗮𝘁𝗵𝗼𝗹𝗼𝗴𝘆: Scientists from Weill Cornell Medicine and Dana-Farber Cancer Institute have developed groundbreaking AI tools for digital pathology. 🔗 https://lnkd.in/dMe5tfrD 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗺𝗲𝗱𝗶𝗰𝗶𝗻𝗲 𝘄𝗶𝘁𝗵 𝗔𝗜! #AI #DigitalPathology #HealthTech #AIInnovation

Some success stories warm your heart a bit more than others 🩷 Very proud of how Lenovo is leveraging AI to help accelerate breast cancer screenings up to 10x faster. With Lenovo x @Nutanix’s HCI solutions, over 120 radiology departments in hospitals have access to solutions that brought a 37.5% increase in early cancer detection. Learn more about the potential of deep learning and image processing methods: lnv.gy/3vSbLRE #ai #wearelenovo #smartertechnologyforall #aiforgood

AI Revolutionizes Cancer Diagnostics 🦠 AI is transforming cancer detection by enhancing diagnostic accuracy and speed, particularly in medical imaging. At the CHEST 2024 meeting, experts highlighted AI’s potential in lung disease diagnosis and brain tumor detection. Techniques like machine learning and deep learning are revolutionizing how radiologists interpret imaging data. AI’s ability to identify features that humans may overlook shows promise, especially for rapid brain tumor assessments via MRI. While challenges remain, AI is poised to improve diagnostic efficiency and accessibility in cancer care. 💻 https://lnkd.in/dNUyVtja ✍ Post prepared by Amir Nakhei | AI Division #AI #CancerDetection #MedicalImaging #AIDiagnostics #HealthcareInnovation #BrainTumorDetection #MedicalAI #CancerCare

Automatic Joint Teeth Segmentation in Panoramic Dental Images using Mask Recurrent Convolutional Neural Networks with Residual Feature Extraction: Can it be useful in Oral Cancer Diagnosis and Management https://lnkd.in/d--QpXQd