Masood Nazari’s Post

🔬 Exciting News from SYNTHEMA! 🚀 We're thrilled to invite you to explore our latest publication: "MOSAIC: An Artificial Intelligence–Based Framework for Multimodal Analysis, Classification, and Personalized Prognostic Assessment in Rare Cancers." This groundbreaking research is a collaborative effort between members of the SYNTHEMA consortium and our sister project, GenoMed4All. 🔍 Key Highlights: 📌 Tackling Rare Cancers: Rare cancers make up over 20% of human neoplasms, presenting unique challenges due to their clinical and genomic complexities. MOSAIC is designed to improve decision-making and treatment strategies for these underserved patients. 📌 Advanced AI Integration: MOSAIC utilizes cutting-edge AI methods, including deep learning for data imputation, UMAP + HDBSCAN clustering for patient stratification, and Gradient Boosting for survival prediction, outperforming traditional statistical techniques. 📌 Explainable and Federated Learning: The framework employs Explainable AI (SHAP) for model transparency and federated learning to enhance model performance and ensure data privacy across multiple clinical centers. 📌 Clinical Validation: Tested on myelodysplastic syndrome (MDS), a rare hematologic cancer, MOSAIC achieved higher accuracy in patient classification and prognostic assessment, demonstrating its potential for broader clinical application. Join us in advancing the fight against rare cancers by reading our publication here: https://lnkd.in/dTZSvh_y Saverio D'Amico #SYNTHEMA #Genomed4All #RareCancers #AIinHealthcare #PersonalizedMedicine #ClinicalResearch #FederatedLearning #ExplainableAI #MOSAICFramework #horizoneurope

Are you Okay with AI helping your doctor? What if it meant being treated faster? OpenAI is expanding its push into healthcare by partnering with startup Color Health to develop an AI assistant that helps doctors with cancer screening and treatment planning. Color Health has created an "AI copilot" using OpenAI's GPT-4 model that can assist doctors in a few keyways: 1.     Generating personalized cancer screening plans based on a patient's risk factors and medical history 2.     Streamlining the pre-treatment process after a cancer diagnosis, which can often take weeks or months before a patient sees an oncologist The goal is to help doctors work more efficiently and focus on clinical decision-making rather than getting bogged down in administrative tasks. While this technology shows promise, there are some concerns. Doctors must fully control the final outputs and decisions because AI models can have biases and "hallucinate" incorrect information. As AI becomes more integrated into healthcare, patients will need to decide if they are comfortable with an AI assisting their doctor. The benefits could be faster diagnosis and treatment, but the risks of AI errors or biases will need to be carefully managed. https://lnkd.in/g5UQN2cS

AI Companies-Personalized Treatment 1. IBM Watson Health • Focus: AI-driven personalized treatment recommendations, particularly in oncology and genomics. 2. Tempus AI • Focus: AI-powered precision medicine through genomic and clinical data to personalize cancer treatment. 3. Freenome • Focus: AI-based early cancer detection and personalized treatment plans using multi-omics data. 4. GNS Healthcare • Focus: AI for personalized medicine by analyzing vast datasets to tailor treatments for individual patients. 5. Deep Genomics • Focus: AI for personalized genetic therapies, using predictive modeling to develop customized treatments. 6. Insilico Medicine • Focus: AI for drug discovery and personalized treatment, especially in aging-related diseases. 7. NantHealth • Focus: AI in personalized cancer care, integrating genomic and clinical data for tailored treatment options. 8. Foundation Medicine Medicine • Focus: AI-driven precision oncology, helping tailor cancer treatments based on genomic analysis. 9. PathAI Diagnostics • Focus: AI in pathology to aid personalized cancer diagnosis and treatment planning. 10. CureMetrix • Focus: AI for personalized breast cancer screening and diagnostic recommendations #AIinHealthcare #PersonalizedMedicine #PrecisionMedicine #HealthTech #MedicalAI #AIinTreatment #HealthcareInnovation #AIinMedicine #SmartHealthcare #Bizcultre 📮 I’ve been deeply immersed in the study of cosmic science and management principles since 2020, and I’ve discovered a fascinating connection to AI. These insights can help enhance the way AI applications are conceptualized and developed. If you’re looking for unique conceptualization for your AI app, I’d love to understand your vision and provide tailored insights based on my research. 🤝 Connect with me or follow my LinkedIn page for more updates on AI, cosmic science, and innovative management strategies. Let’s explore how we can align your AI project with cutting-edge concepts!

THE REVOLUTIONARY POWER OF AI (ARTIFICIAL INTELLIGENCE) AI has shown remarkable promise in detecting cancer at an early stage, with some studies suggesting it can identify cancerous cells up to 5 years before symptoms appear. This is a game-changer in the fight against cancer! What is fascinating is how this AI works. Its algorithms can analyze vast amounts of medical data, including images, genetic profiles, and patient histories, to identify subtle patterns and anomalies that may indicate cancer. This enables: 1. Early detection: AI can detect cancer at a stage when it's more treatable, increasing the chances of successful treatment and survival. 2. Improved diagnosis: AI can help reduce false positives and false negatives, ensuring accurate diagnoses and minimizing unnecessary procedures. 3. Personalized medicine: AI can help tailor treatment plans to individual patients based on their unique genetic profiles and medical histories. 4. Enhanced research: AI can analyze vast amounts of data to identify new cancer biomarkers, leading to better understanding and treatment of the disease. While AI is not yet perfect, I believe this is a very big upgrade in the health care sector. With more collaboration between AI experts, medical professionals and researchers, we are in for greater positive outcomes in the future. Lets stay tuned! #AI #cancerawareness #cancerresearch #breastcancer

Just stumbled upon a game-changer in healthcare research: a case study on metastatic prostate cancer. Here's the scoop: 🚀 𝑹𝒆𝒗𝒐𝒍𝒖𝒕𝒊𝒐𝒏𝒊𝒛𝒊𝒏𝒈 𝑯𝒆𝒂𝒍𝒕𝒉𝒄𝒂𝒓𝒆 𝑰𝒏𝒔𝒊𝒈𝒉𝒕𝒔: 𝑪𝒐𝒉𝒐𝒓𝒕 𝑩𝒖𝒊𝒍𝒅𝒊𝒏𝒈 𝑺𝒖𝒄𝒄𝒆𝒔𝒔 Delving into the recent case study on metastatic prostate cancer research reveals a game-changing strategy. Faced with the challenges of manual data collection across 19 hospitals, 𝐭𝐡𝐞 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧 𝐨𝐟 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐩𝐚𝐭𝐢𝐞𝐧𝐭-𝐟𝐢𝐧𝐝𝐢𝐧𝐠 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 emerged as a strategic breakthrough. This move not only accelerated data collection but ensured precision through Natural Language Processing algorithms. 𝐓𝐡𝐞 𝐨𝐮𝐭𝐜𝐨𝐦𝐞? Swift and continuous feedback to healthcare providers, rapid insights into clinical outcomes and complications, and a remarkable 65% reduction in time compared to manual processes. In numbers, the impact is clear: 📊 10,000+ patient registry in under 2 years. 🔄 53.2% reduction in patients needing inclusion screening. ✔️ 92.3% accuracy in automated data extraction. ⏲️ Extraction completed in 105 mins per patient, down from the former 300 mins. 💼 32,500 hours of work saved, equivalent to 17.4 FTE, and €1,023,333 euros conserved. This case study exemplifies the strategic implementation of technology in healthcare—streamlining processes, enhancing precision, and ultimately advancing patient care. Explore link to detailed case study in the comments section. #healthtechinnovation #healthtech #InnovationInHealthcare 🌐🏥

Google DeepMind CEO, Demis Hassabis, predicts that we are just a couple of years away from having the first AI-designed drugs for major diseases like cardiovascular and cancer. This could be a massive breakthrough in medicine, and AI could play a significant role in making the world disease-free. Learn more about the potential of AI in medicine in this VOA News article. #AIinmedicine #healthtech #futureofmedicine

The major application of AI in near future other than robotics and media will be medicine. According to all my educated research based guesses, medical science will be impacted most by Artificial Intelligence. The next decade will be the decade of medical breakthroughs and just like other technologies, AI will be the backbone of those innovations. Diabetes, cancer, Alzheimer's and any diseases that can be cured by vaccination can be majorly eradicated or controlled using AI. In addition to this, AI will help advance the genetic treatments to a great extent. So, those who are creating utility based AI tools or studying AI, need to think and invest in the right direction. https://lnkd.in/gcPGkK97

AI in Oncology: Reshaping the Landscape of Cancer Care Artificial Intelligence (AI) is transforming oncology, addressing long-standing challenges in cancer care while opening new possibilities for diagnosis, treatment, and patient support. Its integration is shaping a future defined by precision medicine, personalized care, and better outcomes for all. How AI Is Redefining Cancer Care: 🔬 Accurate and Early Diagnosis AI-powered imaging tools analyze medical scans with exceptional precision, identifying subtle patterns often missed by traditional methods. This advancement enables earlier detection, which is critical to improving survival rates and treatment success. 🧬 Personalized Treatment Strategies AI leverages genomic data, electronic health records, and real-time patient information to develop tailored treatment plans. These solutions predict patient responses to therapies, optimizing chemotherapy, immunotherapy, and radiotherapy for maximum effectiveness. 🤝 Improving Patient Engagement and Experience From AI-driven chatbots offering 24/7 support to systems that monitor post-treatment recovery, AI empowers patients with information and better communication, ensuring they are active participants in their care. 💡 Data-Driven Innovation AI excels at analyzing vast datasets, expediting drug discovery, and enhancing clinical trial design. Collaborative approaches in data sharing across institutions are unlocking new pathways for oncology research. 🌍 Ensuring Equitable Care AI is helping to address healthcare disparities by identifying biases in clinical datasets and improving access to quality care in underserved regions. Challenges and Ethical Considerations AI’s integration into oncology isn’t without hurdles. Ethical concerns like data privacy, algorithmic bias, and equitable access require careful navigation. Establishing global data-sharing standards and creating transparent AI frameworks are essential to maximize these technologies' impact responsibly. #AI #CancerCare #OncologyResearch #PersonalizedMedicine #HealthTech #DigitalHealth

AI Revolutionising Treatment Recommendations in Clinical Oncology Important Points: Artificial intelligence (AI) holds transformative potential for clinical oncology, particularly in making personalised and evidence-based treatment recommendations. The review discusses the integration of AI in multidisciplinary cancer conferences, highlighting its capability to analyse complex data and enhance decision-making. Key Learnings: 🔺 Enhanced Decision-Making: AI can process vast amounts of patient and treatment data, facilitating more informed and timely treatment decisions in multidisciplinary cancer conferences. 🔺 Predictive Power: AI applications predict treatment responses and overall survival, offering insights that can tailor individual treatment plans. 🔺 Data Security and Explainability: Addressing challenges like data security and the explainability of AI decisions is crucial for integrating AI into clinical practice. 🔺 Current Limitations: While promising, AI tools must overcome issues related to data representation and the "black box" nature of some AI models to gain wider acceptance. 🔺 Future Prospects: Continued advancements and validation of AI tools are necessary to ensure their reliability and accuracy in real-world clinical settings. Citation: Duwe G., Mercier D., Wiesmann C., Kauth V., Moench K., Junker M., ... Höfner T. (2024). Challenges and perspectives in use of artificial intelligence to support treatment recommendations in clinical oncology. Cancer Medicine, 13, e7398. https://lnkd.in/g-Jg-Chv Application: The insights from this review can guide the development and implementation of AI tools in oncology. AI can enhance clinical decision-making and improve patient outcomes by addressing data security and explainability. Future AI applications may include predictive modelling for various cancer treatments and personalized medicine approaches. Evaluation/My Position: The study effectively outlines AI's potential in oncology, but it must address the "black box" issue and improve data representation. Future research could focus on these areas to ensure AI's successful integration into clinical practice. #AIHealthcare #DigitalHealthInnovation #ClinicalAI #pharma #cancertreatment #clinicalpharmacy

Cancer screening company partners with OpenAI to use GPT-4o. #AIHealthcare 🤝 Download 1 Million Logo Prompt Generator 🔜 https://wapia.in/1mlogo 🤝 Follow us on Whatsapp 🔜 https://wapia.in/wabeta _ ❇️ Summary: Color Health is collaborating with OpenAI to use the GPT-4o model for its new copilot application, which aims to create personalized cancer treatment plans and identify gaps in patient data. The copilot can analyze data in minutes, compared to weeks of delays, and is expected to provide care plans for over 200,000 patients by 2024. While generative AI shows promise in medical analysis, human oversight is still necessary due to the experimental nature of the technology. Hashtags: #chatGPT #AIcancerdetection #GPT4ocancerdiagnosis