kaiko.ai’s Post

Day 2 at the #biomedai #summerschool! Today, we are diving headfirst into the world of AI in #healthcaredelivery! Get ready for a packed day of fascinating talks, lively discussions, and a deep dive into how artificial intelligence is transforming the way healthcare is delivered—from the promises to the pitfalls. We will kick off with Jose Fragata, exploring how will artificial intelligence shape the #FutureOfHealthcare. It is all about the big picture, i.e., where AI is taking us, and the bumps we might hit along the way. Afterwards, stick around for a discussion with João Valente Cordeiro (who will be taking doctor’s perceptions on #AI) and myself (I will be tackling #medicalliability and the #medicalstandardofcare within #AIMedicine), in a session chaired by Duarte Nuno Vieira. Carla Barbosa will then address #medicaldevices and Dimitrios Ioannidis and a session on the US litigation landscape on #GenerativeAI, with Francisca Paulouro as chair. Don’t miss Nickolas Papanikolaou, sharing insights on AI/Radiomics 2.0 in prostate cancer research, a great example of AI making real-world impacts in #medicaldelivery. In the roundtable on AI in medical delivery chaired by Pedro Fontes, I expect some hot takes and expert insights from leading professionals in the field (João Frutuoso, Josué Delgado, Nuno André da Silva and Carolina Brites)- this is where the big debates will happen! After a well-deserved coffee break, Tobias Mahler will explore the rise of #chatbots in healthcare delivery, followed by sessions on advanced AI applications like transforming medical images into diagnostic tags and emotion detection from social media using #LLMs with John McWilliams and Sophia Ananiadou. Finally, wrap up the day with a thought-provoking session on #digitalhealth in the era of AI, by Timos Sellis. From enhancing #PatientCare to navigating complex legal landscapes, we're covering it all. So, buckle up for another day of learning, exploring, and pushing the boundaries of what is possible in healthcare! https://lnkd.in/dcqKdSqh

🚀 EMJ 9.3 Autumn 2024 is Live! 🗞️ Dive into our latest issue for groundbreaking insights on AI’s transformative role in healthcare, including advancements in brain tumor segmentation, the latest updates from clinical trials on osteoarthritis, and essential COVID-19 research. 🔍 Whether you’re looking to promote your research, network with fellow healthcare professionals, or share your expertise, the EMJ team is here to support you every step of the way. Explore the full issue now and connect with us to enhance your impact in the field! 🌟 #Healthcare #AI #ClinicalTrials #COVID19 #MedicalResearch #EMJ

🎉 Excited to Announce Our First Journal Publication! I’m incredibly proud to share that our research paper, "Deep Insights into Gastrointestinal Health: A Comprehensive Analysis of GastroVision Dataset Using Convolutional Neural Networks and Explainable AI", has been published in the highly respected Biomedical Signal Processing and Control (BSPC) journal (Impact Factor: 4.9)! 🎉 Here’s the link to the paper: https://lnkd.in/dCJqEXhE. This paper represents months of collaboration, hard work, and persistence. Our research uses deep learning and explainable AI to address critical challenges in gastrointestinal health diagnostics, including Barrett’s esophagus and colorectal cancer. We’ve taken significant steps toward making AI-driven clinical decisions more interpretable and reliable for real-world use through methods like SHAP and Grad-CAM. Key Contributions: 📌 Addressing the class imbalance in the GastroVision dataset using cutting-edge augmentation techniques, including GANs. 📌 Introducing the Greedy Soup technique for model weight ensembling, boosting performance without increasing inference costs. 📌 Achieving substantial improvements in critical evaluation metrics, underlining the clinical impact of our approach. This milestone wouldn’t have been possible without the unwavering support and dedication of my incredible co-authors and collaborators. I am deeply grateful to Muhammad Fahad for your tireless efforts in experiments and manuscript preparation, Ali Shariq Imran & Mohib Ullah for your invaluable feedback and constant encouragement throughout the process, and Faouzi Alaya Cheikh and Sher Muhammad Daudpota for your critical reviews and constructive suggestions that truly elevated the quality of our work. I’m also deeply grateful to Zenun Kastrati for your detailed insights, which significantly enhanced our research and Subhan Ali Mangi for your essential support with the dataset preparation. This accomplishment marks the beginning of our journey in exploring AI’s transformative potential in healthcare. I look forward to continuing this work and advancing its applications in clinical settings. Here’s to many more milestones! 🚀 #Research #AIInHealthcare #DeepLearning #ExplainableAI #GastroVision #Collaboration #Milestone

For nearly the past 14 years, I have worked with some of the world’s most visionary, passionate scientists in developing new initiatives at Frederick National Laboratory for Cancer Research (#FNLCR). Last month I made the decision to leave FNL to take on an important new opportunity in December to help further improve the lives and outcomes of those affected by cancer. When I reflect on where we started with computing initiatives a decade ago, I am amazed at how far we have all come! Today, we are using #AI, #datascience, and high performance computing to address complex challenges in cancer once thought to be impossible. Over the past many years, I have been fortunate to work with so many wonderful and brilliant colleagues. In 2014, visionary leaders such as Warren Kibbe, Atsuo Kuki and David Heimbrook, who were first to support a new #NCI #CBIIT #HPC initiative for #cancer I was passionate to pursue. Through 2015, we talked with the community and with the #USDepartmentofEnergy (#DOE) to envision how #exascale computing could impact cancer. Working with Warren Kibbe, Ray Bair, Rick Stevens, Paul Messina, Jason Paragas, Dimitri Kusnezov, David Heimbrook and many others, the #NCIDOECollaboration was created. That year, with the help of wonderful colleagues Patricia Kovatch and Thomas Barr, we also organized and held the very first Computational Approaches for Cancer Workshop (#CAFCW) at #SC. In 2016, with initial support from the #NationalCancerInstitute and ultimately from the #CancerMoonshot,℠ we launched the transformative #NCIDOECollaboration with new challenging projects exploring the potential for advanced computing and #AI to transform cancer research and care. Today, the collaboration includes sustainable projects, research community involvement, and resources available to the public from #ATOM #MOSSAIC #IMPROVE and #ADMIRRAL. We explored #FrontiersofPredictiveOncologyandComputing in a series of interdisciplinary workshops from 2016-2018. We spurred international collaborations with the HPC Applications of Precision Medicine (#HAPM) at #ISC from 2017-2022. We launched the interdisciplinary #ComputationalCancerCommunity in 2019. In 2023, we convened national and international thought leaders to envision personalized and integrated model-informed health and wellness with the first #VirtualHumanGlobalSummit exploring medical #digitaltwins. This year, 2024, marks several key milestones, including the launch of the site computational.cancer.gov, expanded community engagement, and we are hosting the #TenthComputationalApproachesforCancerWorkshop (#CAFCW) at #SC24 in Atlanta today! There are so many colleagues to thank for this past decade of transformative team science but there isn’t enough space to list everyone. I am so grateful for the opportunity to have worked closely with all of you over the past decade to improve outcomes, options and quality of life for cancer patients. It has been wonderful to work with each of you! 

Welcome to the third and final day of the #biomedai #summerschool in #lisbon! Today, we are focusing on the interplay between AI and #clinicalresearch; plus, a look at how Europe is shaping #DigitalHealth legislation and policy. It is a full agenda packed with insights, debates, and a chance to look ahead at the future of #AI in #GlobalHealth. Let’s dive in! Start your day with Lee A Bygrave, as he discusses, #information/data quality norms in the ai-medical context, in a session moderated by Graça Canto Moniz. If you have ever wondered about the quality of data behind #aidecisions, this is your session! Later on, the AI & #Biobanking session takes the spotlight next with Michaela Theresia Mayrhofer and Ana Rodrigues, in a session chaired by Helena Canhão, the dean of our Medical School. Ever thought about how AI interacts with #urbanspaces? So, come to listen Bruno Miranda, who will explore this unique angle, moving from natural to AI in our cities. Then, shift gears with Diana Lousa, who will showcase how AI is being used to design tailor-made #antiviral #biopharmaceuticals. All of this in a session moderated by John Pavlopoulos. After lunch, in a session chaired by Dimitri Ioannides, we are diving into the #EuropeanHealthDataSpace with Richard Rak, Ph.D. Rak, followed by a session on secondary data uses in AI, with Paul Quinn. These talks will be crucial for understanding how data drives innovation in #HealthResearch. Then, don’t miss the roundtable on EU digital health legislation and policy-making, where we can expect a lively discussion with leaders like Richard Rak, Ph.D., Paul Quinn and Inês Antas de Barros on shaping the future of digital health in Europe (Chair: Danai Spentzou). Then, shift your focus globally with a roundtable on global health research and AI, featuring insights from Zisis Kozlakidis, Válter R Fonseca Fonseca, and Christina Deligianni Delighiani (Chair: Spyros Kouvelis). Finally, as the day winds down, we will have the session of Adalberto Campos Fernandes, who will present the challenges of health systems, giving us a real-world look at the hurdles and opportunities facing global health today. We will wrap up the conference with final notes and reflections, marking the end of our BioMed AI Summer School. What an incredible journey. Thank you all for making this happen. https://lnkd.in/dFBzKxpa

In an exciting collaboration with Dr. Praveen Meka at Dana-Farber Cancer Institute, Christine Tsien Silvers, MD, PhD, Qing Liu, and Rod Tarrago, MD, we look into the fascinating question of whether AI can reason like a clinician. Our latest blog post explores this topic through the lens of arterial blood gas analyses, a crucial diagnostic tool in healthcare. Arterial blood gas analysis is a complex process that requires clinicians to synthesize multiple data points and apply intricate reasoning to arrive at a diagnosis and treatment plan. In this blog, we discuss how we leveraged advanced AI techniques, including large language models and knowledge graphs, to emulate the clinical reasoning process. Key highlights: 🔹 Understand the challenges and nuances of replicating clinical reasoning with AI 🔹 Explore the potential of AI in augmenting and supporting clinicians' decision-making 🔹 Gain insights into the future of AI in healthcare and its impact on patient care Whether you're a healthcare professional, AI enthusiast, or simply curious about the intersection of technology and medicine, this blog post offers valuable insights. Check it out and let me know your thoughts! [Link to the blog: https://lnkd.in/ehWTAmJ4] #AI #GenerativeAI #Healthcare #ClinicalReasoning #AWS

Exciting news for cancer detection with #AI! Diagnostic accuracy in detecting skin malignancies improved with artificial intelligence (AI) assistance when compared to clinicians without AI assistance, according to research by Isabelle Krakowski, Jiyeong (Jasmine) Kim, Zhuo Ran Cai, MD, Roxana Daneshjou, Jan Lapins, Hanna Eriksson, Anastasia Lykou and Eleni Linos. "The findings of this meta-analysis meaningfully support the potential of AI assistance in improving clinicians' diagnostic performance," the team reports. Visit https://bit.ly/3vSZk8v to read the full paper, published in npj Digital Medicine. #ArtificialIntelligence #DigitalHealth #CancerResearch #SkinCancerDetection #DiagnosticAccuracy

A new $100M research center focused on AI in healthcare has opened in Manhattan.  🔍 This news is part of our 'Top AI in Biotech market stories ' series where we share the latest trends shaping the biotech landscape. Stay tuned for more insights! Mount Sinai Health System has launched the Hamilton and Amabel James Center for AI and Human Health in Manhattan, aiming to integrate AI with precision medicine. The $100-million research center will focus on improving diagnostics, patient care, and genomic discoveries by leveraging one of the largest medical data sets in healthcare. The center integrates AI with precision medicine to improve clinical operations across Mount Sinai’s eight hospitals and 400 clinics. With 12 floors dedicated to research, the $100-million facility will house 40 principal investigators and 250 researchers advancing breakthroughs in genomic health, precision imaging, and disease modeling—essentially combining cutting-edge algorithms with one of healthcare’s largest medical data sets. #HeathcareInnovation #AIinHealth #PrecisionMedicine #ArdigenNews

🔬 Harnessing AI for the Future of Cancer Prediction and Treatment 🧠 A recent breakthrough from MIT demonstrates how robust AI tools are revolutionizing the prediction of future cancer occurrences. These advancements underscore the critical role of cutting-edge technology in clinical research, paving the way for more accurate diagnoses and personalized treatments. At the Clinical Research Learning Network, we are committed to educating the next generation of researchers and healthcare professionals. Our courses are designed to keep you at the forefront of these scientific advancements. Interested in learning more? Explore our courses here: https://buff.ly/3xUVwEt Link to article: https://buff.ly/3cm6TZs #ClinicalResearch #AI #CancerResearch #HealthcareInnovation #MedicalEducation #ContinuousLearning #FutureOfMedicine

🔬🖼️ 𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐌𝐞𝐝𝐢𝐜𝐚𝐥 𝐈𝐦𝐚𝐠𝐢𝐧𝐠: Revolutionizing Diagnostics! - 🧠 Enhanced Accuracy: AI algorithms analyze medical images with precision that rivals human experts, reducing errors and improving patient outcomes.  - ⏱️ Accelerated Analysis: Speed up the diagnostic process with AI's capability to swiftly scan and interpret vast datasets, allowing for timely interventions. - 🔍 Detecting the Undetectable: AI uncovers subtle patterns invisible to the human eye, enabling early detection of diseases like cancer, Alzheimer’s, and more. - 🚀 Pushing Research Frontiers: AI's integration with imaging expands research potential, providing deeper insights into complex biological processes and disease mechanisms. Discover cutting-edge biomedical literature reviews at SciQst: https://www.sciqst.com #MedicalImaging #AIMedicine #HealthcareInnovation #BiomedicalResearch