Deep Genomics’ Post

AI has led to a transformational moment in biomedicine, opening up new possibilities in cell biology. @Chan Zuckerberg Initiative is building one of the largest high-performance computing clusters for non-profit life science research in the world to further this progress. This cluster will power openly available digital models of human cells to allow researchers to collaboratively accelerate their work in understanding the mysteries of our cells and how they interact in systems. CZ Science’s work has been building towards this moment for the last seven years. We’ve supported scientists generating standardized, representative single-cell datasets, built tools that integrate these data and make them widely available so scientists can gather new insights from them, and created the @CZBiohub Network, a unique cross-disciplinary collaborative research model to tackle grand scientific challenges. We won’t do this work alone, and I’m excited to build a team that brings together the scientific and engineering communities to harness the power of AI so researchers across the globe can use it to accelerate discoveries that transform the future of medicine. https://bit.ly/3LvgiP4 #CellBiology #AI #science #biology #innovation #collaboration

Artificial Intelligence is poised to revolutionize scientific research and healthcare. From AI autonomously generating hypotheses and conducting experiments to Google DeepMind's breakthroughs in computational biology, the impact is substantial. AI accelerates drug discovery early disease detection enables personalized treatments although the complexity of biological data remains a challenge. Transforming healthcare towards prevention and early monitoring is essential for the future. Read more about these groundbreaking advancements in the latest Financial Times article. https://lnkd.in/dGzpiNr3 #ArtificialIntelligence #AI #HealthcareInnovation #DrugDiscovery #EarlyDetection #PersonalizedMedicine #ComputationalBiology #ScientificResearch #HealthTech #FutureOfHealthcare #Prevention #DeepMind #Innovation #Biotechnology

🎉 Excited to announce the publication of our research paper on "Empowering Glioma Prognosis With Transparent Machine Learning And Interpretative Insights Using Explainable AI" in IEEE Access Journal! 📝 Our paper aims to establish a reliable technique for diagnosing glioma, a specific type of brain tumor, by leveraging various diagnostic markers and employing a range of machine learning and deep learning approaches, along with explainable AI methods. I extend my heartfelt thanks to my co-author Krishnaraj Chadaga, a dedicated Research Scholar, for his invaluable contribution to our research. Special thanks to Dr. Cifha Crecil Saldanha and Dr. Niranjana Sampathila, PhD, the corresponding authors, for their guidance, unwavering support and mentorship throughout this journey. This paper represents my dedication to advancing research in this critical area, and I look forward to contribute further to the field in the future.🚀 #ResearchPublication #IEEEAccess #MachineLearning #DeepLearning #ExplainableAI #GliomaPrognosis #medicalinformatics

In the ever-evolving landscape of healthcare and technology, Google's #DeepMind sets a new milestone with its #AI system, AlphaMissense. By identifying 89% of key mutations that could potentially cause diseases, DeepMind's innovation promises not just a quicker diagnostic process but also an expedited pathway to effective treatments. This is not merely a technological advancement; it's a leap toward a future where #healthcare is more precise, personalized, and above all, humane. This breakthrough epitomizes the incredible potential of AI in augmenting our capabilities to understand and combat diseases at a molecular level. https://lnkd.in/d3XN8AH2

Morning everyone! Today's blog explores how scientists are using an AI method called deep learning to crack the code of enhancers. Enhancers are small sequences of DNA that don't code for proteins, but do control expression of a gene sequence (sometimes from very far away). This new deep learning method is making it easier to open doors for researchers, and design patient (and cell-specific) therapies by manipulating gene expression. #bioinformatics #celltherapy #deeplearning #AI

Today’s blog explores new research that uses artificial intelligence (#AI) deep learning models to decipher "enhancer codes". Enhancer codes are hidden instructions within our DNA that control cell identity. This breakthrough paves the way for designing cell-specific enhancers, potentially leading to personalized treatments for diseases like melanoma. Read more: https://lnkd.in/eeYTx28c #AI Deep Learning #Deep Learning #Artificial Intelligence #Enhancer RNA #Bioinformatics

If you are using or planning to use AI for your research writing, read this first: The rat with the big balls and the enormous penis – how Frontiers published a paper with botched AI-generated images This article has eventually been retracted but not before becoming the talk of the proverbial research town a few days ago. It may be fine to use AI as a tool, but not as your lazy replacement. You might end up in a more embarrassing situation. https://lnkd.in/e6E86jAC #artificialintelligence #academicwriting #retraction #researchtools

🎉 Exciting News! 🎉 I am thrilled to share that our research paper titled "Segmentation of Liver Tumors by Monai and PyTorch in CT Images with Deep Learning Techniques" has been published! In this work, my co-author Jing Zhang and I delve into the cutting-edge application of deep learning techniques for medical imaging. We leveraged the powerful MONAI framework and PyTorch to enhance the segmentation of liver tumors in CT scans, aiming to improve accuracy and efficiency in medical diagnostics. 🔬 Key Highlights: Utilized state-of-the-art deep learning models to address the challenges of liver tumor segmentation. Integrated advanced image processing techniques to refine tumor boundaries and enhance model performance. Demonstrated the potential of MONAI and PyTorch in developing robust and scalable medical imaging solutions. 📘 Why It Matters: Liver cancer is a critical health issue, and early, precise detection is crucial for effective treatment. Our work contributes to the field by providing a more reliable method for identifying liver tumors, which could potentially lead to better patient outcomes. I am immensely proud of this accomplishment and grateful to all those who supported and collaborated on this journey. Special thanks to my co-author Jing Zhang for the invaluable partnership. 📖 You can read the full paper here https://lnkd.in/emaB73AM. Thank you to everyone who has been a part of this journey. Let’s continue pushing the boundaries of what’s possible in medical imaging and AI! #DeepLearning #MedicalImaging #AI #Healthcare #Research #CTScans #PyTorch #MONAI #LiverCancer