AI2MED’s Post

💡 What about Artificial Intelligence in Croatian Healthcare? A panel discussion from AI2MED ⤵️ #medtech #eHealth #healthtech #digitalhealth

Again or one more about Ai and LMM. I've been diving into some fascinating developments in AI, particularly how large language models (LLMs) are starting to make their mark in healthcare. One of the most exciting things I came across is *OpenCRISPR-1*. This AI-driven technology is creating entirely new gene-editing tools by generating CRISPR variants that are more precise and efficient. Imagine an AI system developing solutions for genetic diseases that were previously out of reach! It’s not just optimizing existing methods—it’s creating completely new ones that might even outperform what we’ve been using so far. This has the potential to revolutionize genetic treatments. You can read more about this innovation here:   https://lnkd.in/e66NTRd6 On the neuroscience side, LLMs are being used in ways that could bridge gaps between different fields like genetics and brain imaging. The sheer volume of data these models can process is beyond what any human could manage, and they’re offering insights that may help tackle complex neurodegenerative diseases. It’s amazing to think that AI could help uncover new treatments by recognizing patterns in data that we couldn’t see on our own. For more insights on this, check out the full article here:   https://lnkd.in/eXM8jb-x However, with all this potential comes a need for caution. These models need to be accurate and free from biases, especially when applied in such critical areas as healthcare. The risks are high, and we need to ensure that these systems are both reliable and ethical before fully integrating them into medical practice. You can explore the challenges and opportunities of AI in healthcare in this detailed review on SpringerLink:   https://lnkd.in/e9-kGN3c I’m really curious to hear if anyone else has been following these trends or has personal experience with AI in healthcare. Have you seen any exciting developments or applications that caught your attention? Let’s share our thoughts and discuss where this might lead in the future! #AIinHealthcare #MedTech #GeneEditing #Neuroscience #HealthcareInnovation

Researchers at Columbia University have created an AI model that can predict gene activity in human cells—a game-changer for everything from cancer research to genetic diseases. In the same way that ChatGPT “understands” human language, this new AI system has learned the "grammar" of cellular behavior. By training on data from over 1.3 million human cells, the model can now predict gene expression in cells it’s never encountered before. These predictions are pretty accurate. This AI is advancing the understanding of pediatric leukemia—predicting how mutations disrupt the behavior of key proteins. This could help unlock new treatments. It also opens possiblities for understanding “dark matter” of our genome, which has remained mostly unexplored, especially in cancer. I can only imagine where this technology will go next—new treatments, personalized medicine, and deeper insights into disease mechanisms. It's an exciting time for science! Columbia University Columbia University Vagelos College of Physicians and Surgeons Herbert Irving Comprehensive Cancer Center Raul Rabadan Alejandro Buendia Xi Fu Carnegie Mellon University Nature Portfolio Nature Magazine Stanford University #AI #ComputationalBiology #GeneExpression #CancerResearch #Innovation #Biotech #PrecisionMedicine #Genetics #DataScience

🔬 Exciting Developments in Precision Medicine! 🧬 The realm of precision medicine is witnessing transformative advances thanks to artificial intelligence (AI) and big data. A recent article in Nature highlights how these technologies revolutionise our approach to understanding and treating complex diseases like cancer. 🌟 Key Insights: - AI enables researchers at institutions like Chiba University to identify patterns in vast amounts of clinical data, predicting disease outcomes with unprecedented accuracy. - The Center for Artificial Intelligence Research in Therapeutics (CAIRT) is at the forefront, leveraging multidisciplinary expertise to stratify diseases and tailor treatment strategies effectively. - This approach moves away from traditional hypothesis-driven research, utilizing data-driven insights to address the heterogeneity and complexity of multifactorial diseases. 👩🔬 The Future: As we continue integrating AI in biomedicine, the potential for personalized medicine grows, offering hope for treatments as unique as the patients themselves. For those involved in #HealthTech, #Biomedicine, or #DataScience, this represents an exciting frontier with numerous opportunities for innovation and collaboration. Read more about how AI and big data are paving the way for future breakthroughs in precision medicine here: https://lnkd.in/d9sxFpRC #ArtificialIntelligence #BigData #PrecisionMedicine #InnovationInHealthcare

10x Genomics is revolutionizing AI in biology by solving data bottlenecks, while the latest FDA approvals and global health updates highlight significant advancements in healthcare. • 🧬 Serge Saxonov of 10x Genomics addresses the challenge of handling vast biological data crucial for AI development. • 💻 AI advancements are driving biotech growth, with companies like Absci collaborating with major cancer centers. • 💊 FDA approves new treatments for liver, kidney, and T-cell lymphoma diseases, expanding patient options. • 🌍 WHO declares mpox a global emergency, emphasizing the need for swift global action to prevent a wider outbreak. • 🧠 Virtual healthcare startups Equip and Midi Health are making waves, addressing eating disorders and menopause care. #AIinHealthcare #FDAApprovals #GlobalHealth - 🧠 AI's impact on drug discovery is growing, with companies like Recursion and Exscientia merging to enhance research capabilities. - 💡 New FDA-approved drugs offer hope for patients with previously limited treatment options. - 🏥 Kaiser Permanente is expanding AI medical note-taking tools across its network, streamlining healthcare processes. - 🚨 The WHO's mpox emergency highlights the critical need for international cooperation in combating emerging diseases. - 🏆 The healthcare sector is buzzing with innovation, from virtual care to AI-driven drug discovery, signaling a transformative era in medicine. InnovationRx: How 10x Genomics Is Fixing The AI Data Bottleneck https://lnkd.in/gevnaprp

While genetic studies have mapped more than 100,000 disease-associated variants in the human genome, we do not know in which cells the majority of these variants are active. Human Cell Atlas will let us know in which cells these variations occur. This project will also advance the applications of ML/AI in disease understanding, epigenetics, drug discovery and many fields.

"Generative AI and Synthetic Genomes: A New Era in Genomics And Medicine" 🚀 Generative AI is transforming fields from text to drug design by generating data from both learned databases and tailored instructions. In genomics, where genomes serve as data and blueprints, this has powerful applications—especially for synthetic cancer genome data. 📄 A recent preprint on OncoGAN (doi: 10.1101/2024.10.17.618896), a generative AI model, caught my attention for its breakthrough in in silico cancer genome generation. Using #GANs and #variational autoencoders (VAEs), OncoGAN creates realistic, #tumor-specific mutation profiles, accurately capturing types, locations, and mutation frequencies. 🧬 By learning from patient data, OncoGAN replicates tumor heterogeneity observed in real genomes. Validated through DeepTumour—a predictive model for tumor types—its synthetic data closely matches the real-world PCAWG dataset, preserving privacy while providing diverse, high-quality training sets for researchers. 🔒 OncoGAN showcases the potential of synthetic data to advance diagnostic tools and AI in oncology, while highlighting the importance of data security. Beyond anonymization, public awareness around genomic data uses is essential. 🔒 As generative AI evolves, the impact on genomic data security is noteworthy. While practices like anonymization and secure computation are essential, there is also a need to increase public understanding around the use and security of genomic information. 🌱 The future of genomics will likely see even more responsible and innovative uses of generative AI. I’m excited to watch this space grow and am curious.... How do you envision GenAI’s role in healthcare, and what are your thoughts on securing genomic data? Dr. Riyaz Syed | SHASHIDHAR JAGGAIAHGARI | Rami Balasubramanian | Anuj Batra | Jeevan Rebba | Centella AI Therapeutics #CentellaAI #CASCADE #AIDrugdiscovery #GenerativeAI #Genomics #Oncology #PrecisionMedicine #GANs #SyntheticData #DataPrivacy #Pharmacogenomics #HealthcareInnovation

𝗜𝗗𝗟 𝗠𝘂𝗹𝘁𝗶-𝗼𝗺𝗶𝗰𝘀 𝗗𝗮𝘆 🌟 𝗔𝗜 𝗠𝗲𝗲𝘁𝘀 𝗢𝗺𝗶𝗰𝘀: 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗶𝗻𝗴 𝗕𝗶𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀! 🌟 Biologists and data enthusiasts, the fusion of #AI with #omics data is unlocking new frontiers in understanding complex biological systems. Here's how cutting-edge AI techniques are transforming the landscape: 🔍 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟):    ✴ 𝘗𝘳𝘦𝘥𝘪𝘤𝘵𝘪𝘷𝘦 𝘗𝘰𝘸𝘦𝘳: #ML algorithms are classifying cell types, predicting disease outcomes, and identifying biomarkers from vast genomic datasets.    ✴ 𝘙𝘦𝘢𝘭–𝘞𝘰𝘳𝘭𝘥 𝘐𝘮𝘱𝘢𝘤𝘵: In #cancer genomics, developing an ML classifier, #OncoNPC, which predicts the origin of cancer of unknown primary (CUP) using next-generation sequencing data. The classifier demonstrated high accuracy in predicting primary cancer types and improved treatment outcomes for patients when predictions were used to guide therapy. (Moonet et al., 2023 https://lnkd.in/dnSZQ24C). 🤖 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗗𝗟):    ✴ 𝘊𝘰𝘮𝘱𝘭𝘦𝘹 𝘗𝘢𝘵𝘵𝘦𝘳𝘯 𝘙𝘦𝘤𝘰𝘨𝘯𝘪𝘵𝘪𝘰𝘯: DL excels in modeling intricate patterns in image and sequence data, crucial for tasks like protein structure prediction.    ✴ 𝘉𝘳𝘦𝘢𝘬𝘵𝘩𝘳𝘰𝘶𝘨𝘩 𝘌𝘹𝘢𝘮𝘱𝘭𝘦: #AlphaFold's DL models have revolutionized protein structure prediction, a game-changer for drug design and understanding biological functions (Jumper et al., 2021 https://lnkd.in/gzHPgHz). 🔗 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗻𝗴 𝗠𝘂𝗹𝘁𝗶-𝗢𝗺𝗶𝗰𝘀 𝗗𝗮𝘁𝗮:    ✴ 𝘏𝘰𝘭𝘪𝘴𝘵𝘪𝘤 𝘐𝘯𝘴𝘪𝘨𝘩𝘵𝘴: AI-driven integration of #genomics, #transcriptomics, and #proteomics offers a comprehensive view of biological interactions and pathways.    ✴ 𝘋𝘪𝘴𝘦𝘢𝘴𝘦 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩: Multi-omics integration is advancing our understanding of complex diseases, paving the way for innovative treatments (Hasin et al., 2017 https://lnkd.in/eEQsR-ck). 💊 𝗧𝗼𝘄𝗮𝗿𝗱𝘀 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗠𝗲𝗱𝗶𝗰𝗶𝗻𝗲:    ✴ 𝘛𝘢𝘪𝘭𝘰𝘳𝘦𝘥 𝘛𝘳𝘦𝘢𝘵𝘮𝘦𝘯𝘵𝘴: AI models predict patient #drug responses based on genomic data, leading to more personalized and effective #healthcare solutions (Rezayi et al., 2022 https://lnkd.in/eyQtg8Gw). 👉 Stay updated on the latest in bioinformatics by following our LinkedIn page! 🌐 Independent Data Lab website for any bioinformatics services: https://lnkd.in/diae-278 Compiled by: Hassiba Belahbib #AI #omics #biotechnology #MachineLearning #DeepLearning #PersonalizedMedicine #genomics #proteomics #bioinformatics #Innovation #drugdesign #multiomics

Fascinating to see the latest human cell atlas efforts published demonstrating the innovation on analytical side (e.g. single cell multi omics method, atlas scalable analysis framework, etc) where we see more and more emerging applied AI/ML based models and also studies with more functional understanding and insights generated around potential of these atlases in hypothesis generation, disease understanding and drug discovery. In current times of high-throughput data era, we need more sound investments and efforts in setting up infrastructure & pipelines for analysis and maintaining them as these are highly complex data that needs high compute & storage. These will be needed else we will not be able to reap in the best out of them specially when we want to think of AI-enabled biomedicine or drug discovery. Among many applications, one of the best thing about these organ specific atlases are to help & guide improved in-vitro experiment efforts with refinement given the potential now of using in-silico perturbational models with AI. We are already seeing some of it and more to come in future but nonetheless this has potential implications to transform target validation, screening & beyond but specifically in cutting down timelines given the catalogue & dictionary of cells one is generating. Hoping these studies will encourage more such efforts and exciting transformative science in the next years. Congratulations to all involved with these efforts across academia and industry. 😃🎉

Leveraging AI in Genomic Research The integration of artificial intelligence (AI) in genomic research is transforming the field, offering unprecedented opportunities to accelerate discoveries and improve healthcare outcomes. AI's ability to analyze vast amounts of genetic data quickly and accurately is revolutionizing how we understand, diagnose, and treat diseases. AI algorithms, particularly #machinelearning and #deeplearning, are adept at identifying patterns and making predictions from complex datasets. In genomics, these capabilities enable researchers to uncover insights that were previously unattainable. AI can sift through large genomic datasets to identify genetic variants associated with diseases, predict how these variants affect biological functions, and even suggest potential therapeutic targets. AI's impact on #precisionmedicine is particularly significant. By integrating AI with genomic data, we can develop highly personalized treatment plans based on an individual's genetic makeup. #AI algorithms can predict how a patient will respond to specific treatments, allowing healthcare providers to tailor therapies that are more effective and have fewer side effects. This approach is especially valuable in treating complex diseases such as cancer, where genetic variations play a crucial role in disease progression and treatment response. At CMB Genomics, a Nairobi-based startup, we are at the forefront of integrating AI into genomic research. We invite researchers, healthcare professionals, and technology partners to join us in leveraging AI to advance genomics. Together, we can drive innovation, improve healthcare outcomes, and make significant strides in understanding and treating diseases. Contact us on +254 743 529576 or info@cmbgenomics.org to learn more about our AI-driven initiatives and explore collaboration opportunities. Let’s revolutionize genomic research with the power of artificial intelligence. #Genomics #AI #ArtificialIntelligence #Research #Healthcare #Innovation #CMBGenomics #Africa #Kenya