Savana’s Post

Our new paper “Automated image label extraction from radiology reports — A review" was recently published in Artificial Intelligence in Medicine 🎉 🔬 This work explores how NLP tools can streamline label extraction in medical imaging. Our decade-long review (2013-2023) covers various NLP approaches, revealing promising avenues for innovation in medical data processing. 🔗 https://lnkd.in/dDkHBzWr #Radiology #NLP #MedicalImaging #MachineLearning #Research

🌟🔍 Discovering the Impact of AI in Cardiology: Insights from an Enlightening Read! 🌟🔍 Recently, I had the pleasure of diving into an insightful article titled "Artificial Intelligence: Revolutionizing Cardiology with Large Language Models". It was a revelation to see how natural language processing (NLP) is reshaping the landscape of cardiology, offering unprecedented benefits across the board - for patients, clinicians, administrators, and researchers. 🚀🩺 The article brilliantly outlines the journey of NLP, shedding light on its history, technical nuances, and the strides made with large language models (LLMs). From automating mundane tasks like generating clinical notes to deploying sophisticated medical chatbots, the scope of AI in enhancing clinical efficiency and patient care is vast and inspiring. 🤖💼 One of the most exciting takeaways was learning about the future possibilities LLMs hold in cardiology - from streamlining decision-making processes to providing rapid insights into disease progression through free text data analysis. But what struck me the most was the emphasis on the importance of fine-tuning these models for specific clinical tasks and ensuring their alignment with users' needs through reinforcement learning. Ensuring safety and efficacy in their application is paramount. 🎯👥 This read has left me optimistic about the potential of AI to revolutionize cardiac care, and I'm eager to see how these technologies will continue to evolve and impact the field. For anyone interested in the intersection of AI and healthcare, this article is a must-read! 👉 https://lnkd.in/dai7KXjQ Your thoughts on the safe and effective implementation of these technologies are welcome. #GenerativeAI #MedTech #Cardiology #Healthcare #Innovation #likeabosch

Join us for a webinar on Sunday, November 12, 11:00 AM ET to explore Bionl.ai, your no-code biomedical research platform. Learn how you can: - Analyze your data. - Review and search the literature. - Visualize your analysis. without writing a line of code! To register for the webinar, please visit this link: https://lnkd.in/eadwXM5a We look forward to seeing you there! #Bionl.ai #NLP #Biology #Webinar

A recently published paper has applied natural language processing (NLP) to the creation of #radiology reports with the aim to evaluate if it could help clinicians achieve more structure reporting in the field. And the results are promising ➡️ https://lnkd.in/epXmCdTx On the other hand, clinically available #AI radiology #software, like Quantib Prostate, can already include features to optimize structured reporting in the radiology field. Curious to know more?➡️ https://lnkd.in/ee_uXd3N

#NLP methods can help physicians to automatically identify and extract relevant information by analyzing #radiology text reports, collect large radiology image datasets as well as automate image collection and annotation. Via https://lnkd.in/ghyvJMXZ #naturallanguageprocessing #medicalimaging #deeplearning #imageanalysis #aiforhealthcare 

Hospitals and clinics perform a large number of screening tests for early illness detection and improve patient’s chances of a full recovery. However, they struggle to prioritize patients effectively and to advance them to treatment. Artificial Intelligence comes a paramount tool to assist medical staff with automatized pathology detection. The abdomen is a critical anatomic region, connecting all regions of the body and carrying many organs with distinct characteristics. This makes it very susceptible to symptoms, becoming a bottleneck in the prioritization process. This study presents a methodology to improve a multi-class classifier by increasing the samples in the input dataset with linguistic analysis. This session was presented by Walter Silva Martins Filho – Senior Data Scientist at NeuralMed at #Healthcare #NLPSummit 2024 Watch an entire video here: https://lnkd.in/dS_c6bSx #LargeLanguageModels #MedicalAIApplications, #AIinHealthcare #LLMs #HealthcareLLMs #GenerativeAI #HealthcareAI #MedicalLLMs #nlp

The AI in Health care course by MIT is great for all 'Bridgers' interested in linking AI innovations and the healthcare industry to accelerate diagnosis and improve patient care. The topics explored include: - Utilizing AI for disease diagnosis and patient monitoring - Harnessing Natural Language Processing (NLP) in healthcare contexts - Unpacking the importance of interpretability in Machine Learning - Patient risk stratification and optimizing clinical workflows - Real-life case studies, including breast cancer prediction models - Crafting our own AI framework to tackle healthcare problems of choice. #AI #HealthcareInnovation #MIT #Bridgers

Another scientific success story on how Savana is applying Artificial Intelligence in real use cases in Healthcare today!! Through the seamless integration of Natural Language Processing (NLP) and AI techniques on Clinical Data, on the realm of Rheumatoid Arthritis, Savana has been able to identify interstitial lung disease as a prevalent comorbidity in rheumatoid arthritis patients. ➡ You can read the full article here: https://lnkd.in/dfFWzjiK #clinicalnlp #aiinhealthcare #emr #rheumatoidarthritis #clinicaldata

From Savana we continue creating Artificial Inteligence algorithms for real clinical cases, to boost clinical outcomes and bringing innovation to the healthcare professionals. #ai #aihealthcare #digitalhealth #research #clinicaldata #clinicalresearch

Are you looking to extract more meaningful data from patient records without the massive resource price tag?  Let's connect at #CAR2024! Across Canada, healthcare teams work every day to enhance patient care but there is a lingering problem. Due to ever-increasing resource costs, healthcare teams have to spend endless human hours and precious funding on work that can (and some argue should) be automated. What if tools could de-identify data - critical for research collaboration? What if there was a way to advance lung cancer screening, enabling earlier detection of pulmonary nodules in radiology reports, with technology that's available today? Watch our presentation at #CAR2024 - where we’ll share details on some of our most recent findings on the use of Natural Language Processing (NLP)! We Want to Hear from you!  Do you have the same challenges?  Perhaps you’re using NLP in interesting ways?  Regardless, please share what you’re doing. Like, share, and comment - let's help AI and NLP revolutionize healthcare together. #healthcareinnovation #medicaltechnology #radiology #AIinHealthcare #CARJ #NER Canadian Association of Radiologists