Vipin Thazhissery’s Post

Exciting advancements in cancer diagnosis! 🎉 Researchers at MIT and ETH Zurich have developed an AI model that can identify the stages of ductal carcinoma in situ (DCIS), a type of preinvasive breast cancer, using simple and affordable tissue images. This breakthrough could streamline the diagnostic process, reducing the need for expensive, labor-intensive tests and helping clinicians focus on more complex cases. The potential of AI in healthcare is immense—improving accuracy, efficiency, and patient outcomes. This is just the beginning, and I’m excited to see how AI will continue to revolutionize cancer detection and treatment! What are your thoughts on using AI for healthcare innovations? https://lnkd.in/dJju3StQ #konfio_hackai #aiaiai #AIAIAI #AI #MachineLearning #LLMs #DataScience #BreastCancer #HealthcareInnovation #cancer #medicine

🌟 Just read about an exciting AI development from MIT and ETH Zurich! Researchers have created an AI model that accurately identifies stages of ductal carcinoma in situ (DCIS), a type of preinvasive breast tumor. This breakthrough could revolutionize cancer diagnostics by reducing overtreatment and improving precision in identifying high-risk cases. The potential applications extend beyond breast cancer to other cancers and neurodegenerative diseases. Truly inspiring work! #AI #HealthcareInnovation #BreastCancer #MachineLearning #HealthTech Read more about it here: MIT News ↔ https://lnkd.in/ggRH2Cv5

Incredible work by Massachusetts Institute of Technology using #AI to identify tumors early and potentially preventing over-treatment in the future. Ductal carcinoma in situ (DCIS) is a type of preinvasive tumor that sometimes progresses to a highly deadly form of breast cancer. It accounts for about 25 percent of all breast cancer diagnoses. Because it is difficult for clinicians to determine the type and stage of DCIS, patients with DCIS are often overtreated. To address this, an interdisciplinary team of researchers from #MIT and #ETH Zurich developed an AI model that can identify the different stages of #DCIS from a cheap and easy-to-obtain breast tissue image. Their model shows that both the state and arrangement of cells in a tissue sample are important for determining the stage of DCIS. Researchers can use techniques like multiplexed staining or single-cell RNA sequencing to determine the stage of DCIS in tissue samples. However, these tests are too expensive to be performed widely. This is where #AI can really shine in patient diagnosis and Clinician decision support. #dayone #ai #insights #oncology https://lnkd.in/grDPUnGb

AI is making progress by leaps and bounds, and I believe this is just the beginning. The latest breakthrough from MIT researchers on early detection certain types of breast cancer just highlights the AI's transformative potential, What it does is ;  • It can detect breast cancer up to 5 years before clinical diagnosis! • Analyzes chromatin images to identify 8 distinct cell states in early-stage cancer • Can detect cancer indicators invisible to the human eye and much more. Just a few years ago, this level of early detection seemed like science fiction. Now, it's on the cusp of revolutionizing cancer diagnosis and potentially saving countless lives. We're not just improving existing processes – we're unlocking entirely new capabilities that were previously unimaginable. #ai #humans #innovation #technology #future #AIAdvancement #FutureOfHealthcare #TechForGood #AI #Cancer https://lnkd.in/dak2DjDY

Researchers at the Paul Scherrer Institute (PSI) achieved an advance with the development of a test enabling early detection of cancer. The ability to detect a developing tumour at a very early stage and to closely monitor the success or failure of cancer therapy is crucial for a patient’s survival. A breakthrough on both counts has now been achieved by researchers at PSI. Using artificial intelligence (AI), the scientists were able to distinguish between healthy and sick people with about 85 percent accuracy. In addition, they managed to correctly determine the type of tumour disease – melanoma, glioma, or head and neck tumour, which is the first time anyone, worldwide, has achieved this. https://lnkd.in/e2tYTq8J #cancerresearch #artificialintelligence #seniorcare

AI model identifies certain breast tumor stages likely to progress to invasive cancer A new AI model developed by researchers from Massachusetts Institute of Technology (MIT) and ETH Zürich can accurately identify the stages of ductal carcinoma in situ (DCIS), a preinvasive breast cancer, from simple breast tissue images. This model, which considers both the state and spatial arrangement of cells, aims to address the common issue of overtreatment by offering a more precise diagnosis. The research highlights that spatial organization of cells is crucial for determining the cancer stage. This model, trained on a large dataset, showed high agreement with pathologists' evaluations and could streamline the diagnosis process. This AI tool, which can be adapted for other cancers and neurodegenerative diseases, represents a significant advancement in using affordable imaging techniques for accurate disease staging. Read more here: https://lnkd.in/eKcaJn93 #AI #Cancer #BreastCancer #AIHealthcare #MedicalImaging #CancerDiagnosis #MIT #ETHZurich

🧐Explore the latest on Circulating Tumor Cells (CTCs) as liquid biopsies in our new study, revealing cutting-edge advances and their clinical relevance in cancer management. #CancerResearch #LiquidBiopsy #CTCs Access the full paper here👉 https://lnkd.in/d2fy5TPT

AI Algorithm Shows Potential in Identifying Women at Risk for Breast Cancer AI's role in healthcare continues to expand, and a new study highlights its potential in breast cancer screening. Researchers analyzed the performance of an AI algorithm (INSIGHT MMG) that assigns risk scores based on mammogram data. By comparing consecutive scores, the study showed that increasing AI scores correlated with a higher likelihood of future breast cancer diagnoses. With the potential to improve early detection and outcomes, this technology could transform cancer screening practices. However, more research on diverse populations is needed. #BreastCancerAwareness #ArtificialIntelligence #HealthcareInnovation Link to article: https://lnkd.in/eu7rs5at

🔍 In case you missed it, researchers have made an exciting breakthrough in cancer treatment with the development of a nanosurgical tool. This innovative approach allows for precise targeting and biopsy of cancer cells that survive chemotherapy, opening new doors for understanding and treating the most stubborn forms of the disease. We are always excited to share pioneering developments that could transform patient care. This represents the kind of innovative work we admire and support in the medical community. 🌐 Discover more about how this technology is paving the way for new cancer treatments: Read about the nanosurgical tool: https://lnkd.in/en3gna8u #CancerResearch #InnovativeMedicine #FloMedical

3D maps of cancer produced by an NIH initiative provide critical information on how tumors develop, spread, and respond to treatments. These maps provide a better understanding of the development and progression of cancer, which could eventually lead to new prevention and treatment strategies. #cancer #tumor #prevention