Kelyon’s Post

Ageing isn’t just about adding years—it’s about thriving in good health. AI is transforming how we understand and combat age-related challenges. From analyzing vast biological datasets to predicting health risks, AI drives breakthroughs in drug discovery, precision medicine, and real-time health monitoring. Personalized interventions? Check. Early disease detection? Absolutely. Enhancing both lifespan and healthspan? That’s the goal. 👉 We’re proud to be partners in the AI2MED project, revolutionizing the future of health. Read more about how AI is revolutionizing longevity and discover the impact of AI2MED: https://lnkd.in/deTu2ueg

AI Revolutionizing Longevity The science of #angeg is undergoing a transformative shift, driven by #AI and its profound impact on biomedical research. Ageing is influenced by genetics, #lifestyle, environment, and access to #healthcare, but AI is unlocking new possibilities for understanding and combating age-related decline. By distinguishing between #lifespan (years we live) and #healthspan (the quality of those years), we can aim for longer, healthier lives. AI accelerates research by analyzing vast datasets from genomics and proteomics to uncover #biomarkers of ageing. It has revolutionized drug discovery, pinpointing compounds that target ageing pathways and is transforming #personalized medicine. With predictive analytics, AI forecasts disease risks and recommends tailored interventions, ensuring health strategies align with individual profiles. In diagnostics, AI detects early signs of #diseases through imaging tools and wearable technology, enabling timely interventions. It also supports lifestyle optimization, offering insights into diet, exercise, sleep, and stress management to enhance both healthspan and lifespan. Moreover, AI is indispensable in tackling age-related diseases, advancing treatments for conditions like Alzheimer's, Parkinson's, and cancer. Yet challenges remain, including data privacy, algorithmic bias, and accessibility. Ageing is a complex, systemic process, but AI's modelling capabilities help integrate diverse mechanisms, offering a holistic understanding. The goal isn't just to extend life but to improve its quality, redefining ageing in the 21st century. Read more 👉 https://lnkd.in/deTu2ueg Università di Pavia Griffith College Dublin Smion BIRD Incubator Univerzitet Crne Gore Sveučilište Algebra TIB – Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek Università degli Studi di Napoli Federico II Kelyon Jozef Stefan Institute Royal College of Surgeons in Ireland (RCSI)

Could #AI be the key to finding a cure for #diseases like Alzheimer’s? With its ability to analyze vast amounts of data quickly, AI is transforming the way researchers approach complex diseases. Alzheimer's, a neurodegenerative disorder that currently has no cure, presents a significant challenge because its causes are not fully understood. However, AI is helping to unlock new insights. AI powered #algorithms can analyze brain scans, genetic information, and clinical #data to identify early signs of Alzheimer’s that may be missed by traditional methods. By recognizing patterns in these datasets, AI can #predict disease progression and even highlight potential targets for treatment. This means researchers can focus on developing therapies that may slow or stop the disease earlier in its course. Moreover, AI can accelerate drug #discovery. Traditional research methods are time consuming and costly, but AI can rapidly screen thousands of compounds, predicting which ones might be effective against Alzheimer’s. This could speed up the search for a cure or treatments that improve quality of life for patients. While we’re not there yet, the future looks promising. AI’s potential to revolutionize Alzheimer’s research brings hope for breakthroughs that could change millions of lives. #Unboxmed #Research

The success of these pioneering #students underscores the importance of investing in #education and research that directly impacts societal well-being. Their dedication to advancing #AI in #healthcare highlights the potential for transformative changes in how diseases are detected and treated, ultimately improving patient outcomes and quality of life. https://lnkd.in/gHbYVnw9

Did you know that Artificial Intelligence (AI) is making groundbreaking strides in the fight against Alzheimer's Disease? Alzheimer's affects millions worldwide, causing memory loss, cognitive decline, and immense emotional strain on families. But there's hope on the horizon! AI technology is proving to be a game-changer in early diagnosis and treatment. Here's how AI is revolutionizing Alzheimer's care: Early Detection: AI algorithms analyze brain scans and genetic data to identify early signs of Alzheimer's long before symptoms appear. This early detection allows for timely intervention, which could slow the disease's progression. Personalized Treatment: AI helps in developing personalized treatment plans by analyzing patient data and determining which therapies are most likely to be effective for an individual. This personalized approach can potentially improve patient outcomes. Drug Discovery: AI accelerates the search for new drugs by rapidly sifting through vast amounts of data. This speeds up the process of identifying promising compounds that could lead to new, effective treatments. Monitoring and Support: AI-powered apps and devices can assist patients with daily tasks, monitor their health, and provide caregivers with real-time data. This enhances the quality of life for both patients and caregivers. The impact of AI on Alzheimer's Disease is nothing short of transformative. As we continue to innovate and harness the power of AI, we move closer to a future where Alzheimer's might be detected early, managed more effectively, and eventually, cured. Let's stay informed and support the incredible advancements in AI technology that could one day change the lives of millions. Follow me Ronita De, Ph.D for more updates on healthcare innovation. Keep reading! https://lnkd.in/gEKka-88 #AlzheimersAwareness #ArtificialIntelligence #HealthcareInnovation #BrainHealth #DHPSP #Sciencecommunication

Hypothesis Generation in Medicine using LLM (ChatGPT, Gemini, Llama etc) General Hypothesis Generation in Medicine 🚀 "What if AI could predict disease outbreaks by analyzing social media trends and environmental data in real-time? How could this change public health?" 🧬 "Could analyzing genetic mutations across diverse populations unlock clues to cure rare diseases? What role could AI play in this journey?" 💊 "If drugs could be tailored to an individual's microbiome, would we witness better treatment outcomes? What are the first steps to making this a reality?" 🌍 "Can environmental data, like air quality and water pollution, be directly correlated with genetic predispositions to chronic illnesses? How do we start testing this?" Hypotheses in Diagnostics 🩺 "If machine learning models analyzed historical diagnostic errors, could we design better diagnostic workflows to minimize misdiagnosis?" 🔬 "Could wearable devices, coupled with AI, predict diseases years before clinical symptoms arise? What are the hurdles in validating such models?" 🧠 "Can emotional health data from patient conversations provide insights into physical disease progression? What ethical concerns should we address first?" Hypotheses in Genomics 🧬 "Could AI uncover undiscovered patterns between non-coding regions of DNA and chronic diseases? How would this reshape genetic research?" 🔎 "If we used AI to analyze the differences in X and Y chromosome activity across populations, what new insights into gender-specific diseases could emerge?" ⚡ "Could real-time DNA editing simulations accelerate our understanding of CRISPR's potential limitations and risks? What role would AI visualization tools play?" AI and Data Integration 📊 "Can LLMs extract latent connections between unrelated medical studies, leading to breakthrough treatments? How do we quantify the validity of such insights?" 🌌 "If we integrated social determinants of health with genomic data, could AI models improve predictions of disease prevalence in underserved communities?" 🔗 "Can AI uncover correlations between mental health disorders and metabolic diseases by combining diverse datasets? What research gaps does this bridge?" Hypotheses in Drug Discovery 💊 "Could an AI analyze failed drug trials to identify new applications for previously discarded compounds? How would this impact the speed of drug discovery?" 🔍 "If we trained AI models on the biochemical structures of venom toxins, could they suggest novel drug designs? What would be the challenges in this approach?" Hypotheses in Public Health 🌍 "What if AI could predict patient outcomes based on regional healthcare disparities? Could this influence policy decisions globally?" 🤝 "Can AI map disease clusters in real-time and propose actionable public health interventions? What role does data transparency play?" 🏥 "If patient-doctor interaction data were anonymized and analyzed, could we create a model to enhance patient satisfaction and adherence?"

The research spans institutions across the globe, including Stanford University (USA), Peking University (China), Harvard Medical School (USA), University of Tokyo (Japan), and University of Glasgow (UK), showcasing a collaborative international effort in viral evolution prediction. Key People: Brian Hie, a computational biologist from Stanford University, applies large language models to study viral mutations. Yunlong Cao from Peking University conducts experiments on how mutations help viruses evade antibodies. Debora Marks from Harvard developed EVEscape to simulate spike protein variants. Jumpei Ito from the University of Tokyo created the CoVFit model to predict variant fitness. David Robertson, a virologist at the University of Glasgow, highlights the transformative role of AI-based tools like AlphaFold. Technology Used: AlphaFold (DeepMind), ESM-2, and ESMFold (Meta) are AI tools enabling protein-structure predictions. EVEscape, created at Harvard, designs SARS-CoV-2 spike protein variants for vaccine testing. CoVFit, developed by Ito’s team, predicts the relative fitness and spread of SARS-CoV-2 variants using vast datasets. Key Highlights: AI allows researchers to predict which mutations will make viruses more transmissible or antibody-evasive. Tools like EVEscape and CoVFit have been instrumental in identifying potential future variants and guiding vaccine development. Achievements: CoVFit successfully predicted the fitness of several SARS-CoV-2 variants, including the globally dominant JN.1 variant and its mutations, well before they emerged in populations. Conclusion The use of AI in predicting viral evolution is revolutionizing pandemic preparedness by enabling scientists to anticipate how viruses like SARS-CoV-2 may evolve. Models like EVEscape and CoVFit provide critical insights into mutation impacts and variant fitness, allowing researchers to design vaccines and antiviral treatments more proactively. However, the technology is still developing and requires further refinement and data to achieve long-term forecasts. As this field advances, it holds immense potential to mitigate the impacts of future pandemics by staying ahead of viral evolution. Stay ahead in AI! Follow AIPOOOL and subscribe to our free newsletter for the latest updates! #ai #chatgpt #aitools #openai #aitips #machinelearning #artificialintelligence #deeplearning #generativeai #medical #doctor #health

🔬 The Convergence of AI and Biotechnology: A New Era in Medicine 🤖 The integration of Artificial Intelligence (AI) and Biotechnology is reshaping the frontiers of medical science and healthcare, offering novel solutions to some of the most challenging questions in human health. As a student passionate about these fields, I am inspired by how this interdisciplinary collaboration is accelerating the pace of innovation and transforming patient outcomes. 🌍 AI's ability to analyze complex, multidimensional datasets with unparalleled precision is driving advancements across key areas of biotechnology: 🧬 Genomics and Personalized Medicine AI algorithms are transforming the analysis of genomic data, enabling the identification of disease-associated variants and unraveling epigenetic modifications. This knowledge is central to personalized medicine, where AI guides clinicians in designing individualized treatment regimens, optimizing therapeutic efficacy, and reducing the risk of adverse reactions. 💊 Drug Discovery and Development The traditional drug discovery process is time-consuming and expensive. AI, however, is revolutionizing this pipeline by predicting protein-ligand interactions, simulating pharmacodynamic and pharmacokinetic properties, and identifying promising drug candidates faster. Remarkably, AI is also repurposing existing drugs to target diseases such as cancer and neurodegenerative conditions, expediting the availability of life-saving treatments. 🩺 Diagnostics and Medical Imaging AI-powered deep learning models are enhancing diagnostic accuracy in areas like oncology, where they detect biomarkers from histopathological slides and predict tumor progression. In radiology, AI systems are assisting in identifying subtle abnormalities in imaging data, reducing diagnostic errors, and supporting early disease detection. 🧪 Synthetic Biology and Biomanufacturing In synthetic biology, AI is enabling the design of custom gene circuits and facilitating the creation of bioengineered products, including vaccines, therapeutic proteins, and sustainable biomaterials. AI-driven bioengineering is also advancing the development of organoids and tissue scaffolds, opening new avenues for regenerative medicine. 🦠 Epidemiology and Global Health AI’s role in tracking and modeling disease outbreaks, such as COVID-19, highlights its importance in public health. By predicting disease dynamics and optimizing resource allocation, AI is instrumental in crafting proactive and effective interventions. This convergence marks a shift from reactive to predictive and preventive medicine, ushering in a new era where technology and biology work hand in hand to solve pressing medical challenges. #AI #Biotechnology #Genomics #DrugDiscovery #SyntheticBiology #TranslationalMedicine #HealthcareInnovation #LifelongLearner