Published paper on disease detection using ML and DL techniques in IEEE Xplore

🎉 I’m thrilled to share that our research paper "Efficient Machine Learning & Deep Learning Approaches for Disease Detection" has been published in IEEE Xplore after being presented at ICCSP 2025. This work was done in collaboration with my amazing teammates Prashanth Raj B and Sai Koushik Reddy Vatam, under the valuable guidance of Dr. Bhulakshmi Bonthu from the Department of Information Security, VIT Vellore. Our research focuses on applying machine learning and deep learning models for the early detection of diseases like breast cancer, heart failure, pneumonia, and diabetes. The models achieved promising accuracy levels, showing potential to support timely diagnosis and medical interventions. 📄 You can check out the publication here: https://lnkd.in/gGdipygu Excited to keep exploring the intersection of AI and healthcare and contribute further to impactful research! #MachineLearning #DeepLearning #HealthcareAI #Research #IEEE

Marylyn Ritchie has been appointed as the chief artificial intelligence officer at the Medical University of South Carolina (MUSC). Ritchie, previously at the University of Pennsylvania, will lead MUSC's AI and biomedical informatics initiatives starting November 3. She will focus on integrating AI across education, research, and patient care, aiming to improve patient outcomes and eliminate health disparities. Ritchie is recognized for her work in translational bioinformatics and has authored over 500 publications. Read more: https://lnkd.in/eiDk2zTj 📰 Subscribe to the Life AI Weekly Newsletter: https://lnkd.in/eC5-u69w #ai #artificialintelligence #ainews #biotech #healthcareai

🌟Proud to share a Milestone 🌟 Our paper titled “Detection of Lung Cancer using Histopathological and CT Scan Images,” was presented at the 2025 Global Conference on Information Technology and Communication Networks (GITCON), organized by IEEE Bangalore Section in KLS Gogte Institute of Technology,Belgavi,India, and has been selected for publication in the renowned IEEE Xplore Digital Library.🎉 This work was a collaborative effort with my co-authors,Fatima Shekh ,Sujal Yavagal ,and Nihaal under the valuable guidance of Dr. Manohar Madagi, Computer Science and Engineering, KLE Technological University, Hubballi. We proposed a hybrid AI-based framework for lung cancer detection using multi-modal imaging (Histopathological slides + CT scans). Our approach uses a dual model approach that is traditional feature extraction (HOG & DAISY) and deep learning (MobileNetV2) for feature learning, followed by XGBoost classification. This enhanced diagnostic accuracy to 99%, making it suitable for deployment in clinical and telehealth environments. This achievement marks an important step in leveraging AI for healthcare innovation, and I look forward to exploring more impactful research ahead! 🚀 #IEEE #GITCON2025 #AI #DeepLearning #MedicalImaging #HealthcareInnovation #LungCancerDetection #ResearchPublication #KleTu

✨ Excited to share some of our recent research contributions in the field of medical imaging and AI for intracranial aneurysm management! 📌 Journal Publications  – "Computationally efficient dilated residual networks for segmentation of major cerebral vessels in MRA." Network Modeling Analysis in Health Informatics and Bioinformatics 14, no. 1 (2025): 95.  – "Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease." Scientific Reports 15, no. 1 (2025): 1-9.  – "Computer-Aided Volumetric Quantification of Pre- and Post-Treatment Intracranial Aneurysms in MRA" IET Image Processing, (2025). These works reflect our ongoing efforts in developing AI-driven tools for diagnosis, quantification, and post-treatment monitoring of intracranial aneurysms. Special thanks to my co-authors, supervisors, and neurointerventional radiologists who contributed their invaluable expertise, clinical insights, and continuous support in making this research possible. Together, we are working towards bridging the gap between AI innovation and clinical practice to improve patient outcomes. #AI #MedicalImaging #Aneurysm #DeepLearning #IEEE #Research #Teamwork

🚀 Thrilled to share that our research paper has been published in Frontiers in Artificial Intelligence (Medicine and Public Health section)! 🎉 📄 Title: Machine Learning-Driven Lung Cancer Risk Prediction: Evaluating Augmentation Strategies with Explainable AI 🔗 Read here Lung cancer continues to be a leading cause of cancer-related mortality, making early and accurate prediction essential. However, the challenge of class imbalance in clinical datasets often limits model reliability. In this study, we: ✅ Explored advanced data augmentation techniques (including K-Means SMOTE) ✅ Benchmarked multiple ML classifiers for prediction accuracy ✅ Leveraged Explainable AI (LIME) for model interpretability and transparency ✅ Achieved 93.55% accuracy and 96.76% AUC-ROC with K-Means SMOTE + MLP 🔍 Why this matters: Our findings show how augmentation strategies can significantly enhance predictive power in imbalanced clinical datasets—paving the way for more reliable AI-driven diagnostic models. While this is an early methodological study (on a small dataset), it lays the groundwork for scaling to larger, real-world medical applications. I’m incredibly grateful to my co-authors Pavithran M S and Anirban Chakrabortty, mentors, and the team at Vellore Institute of Technology (VIT), Chennai for their support and collaboration. 🙏 #ArtificialIntelligence #MachineLearning #HealthcareAI #LungCancerPrediction #ExplainableAI #Research #FrontiersInAI

🌟Thrilled to share about our ₹6 Lakh Funded Research Project Our research project on Sickle Cell Disease (SCD) classification using deep learning techniques for histopathological images has been published on IEEE Xplore. 📑✨ This work represents a meaningful step towards leveraging AI-driven medical imaging for better diagnosis and patient care. The project was made possible with generous funding support of ₹6 lakhs from the Institution of Eminence (IoE), University of Delhi 🎓 and in close collaboration with Balco Medical Centre, whose medical expertise added immense value. Grateful to my co-authors, collaborators, and mentors for their unwavering support throughout this journey. 🙏Dr. Arun Kumar Dubey, Dr. Achin Jain#AI #DeepLearning #MedicalImaging #SickleCellDisease #IEEE #Research #Collaboration #HealthcareInnovation

💡 𝗧𝗵𝗲 𝘀𝗺𝗮𝗿𝘁𝗲𝘀𝘁 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 𝗶𝗻 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝗶𝘀 𝘂𝘀𝗲𝗹𝗲𝘀𝘀 𝗶𝗳 𝗶𝘁 𝘀𝗼𝗹𝘃𝗲𝘀 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. When I first got into healthtech, I was eager to apply all my computer science tools, complicated networks, cool algorithms, big ideas to make an impact in biomedicine. But I quickly realized: if no one actually needed what I was building, then it didn’t matter how “smart” the solution was. That’s why I started taking every biomedical course I could. Not just tech-related ones like bioinformatics and cheminformatics, but also classes far outside my comfort zone, including Biomedical Imaging, Tissue Engineering, and more. (At this point I could almost say I’ve earned a biomedical minor. 🧬) Those classes were eye-opening. In fact, it was during Biomedical Imaging that I discovered the challenges of fluorescence microscopy. That problem sparked my first publication 🔬 and eventually led to my current projects in biomedical image processing. Now, whenever I step into a new domain, I don’t start with brainstorming solutions. I start by treating myself as a newcomer, listening, learning the field, and understanding its pain points. The solutions that emerge afterward are almost always more impactful (and very different from my first ideas). 🌟 In the end, domain knowledge is what turns good ideas into meaningful ones. 🤔 Curious, what’s the most unexpected thing you’ve learned when stepping outside your comfort zone? 📸 P.S. This is me during my Tissue Engineering course, doing Frankenstein-level experiments and looking way too excited about it. #HealthTech #Biomedicine #BiomedicalImaging #ArtificialIntelligence #MachineLearning #Innovation #Research #STEM #CareerJourney #LifelongLearning

The thalamus, being a crucial region for sensory processing and multi-sensory integration with both bottom-up and top-down connectivity, is in a powerful anatomical and functional position to guide cortical processes. While past thalamic research has focused mostly on pure sensory processing (i.e., their relay role), the importance of non-relay functions (e.g., cognition) has recently been emphasized, but much less understood. We are especially interested in the anterior thalamic nuclei (ATN) and its cell types, which have been implicated in long-term memory formation, attention, and spatial navigation. In this talk, I will describe our work aimed at developing tools to genetically access ATN cell types with high specificity, investigate their role in contextual learning and generalization, and how computational models along with in vivo calcium imaging is helping us uncover similarities vs. differences between the ATN and the broader cognitive network (i.e., cortex and hippocampus). We believe that these complementary approaches have the potential to reveal novel cell type- and functionally-distinct subnetworks within the ATN, which underlie cognitive functions.

🌟 Delighted to Share 🌟 I am pleased to announce that our research paper, “Enhanced PCOS Detection Using CNN Multi Variable Feature Selection and Binary Classification for Precise Diagnosis,” has been published in the IEEE Xplore Digital Library under the 2025 6th International Conference, and is indexed in Scopus. This work highlights the potential of Artificial Intelligence and Deep Learning in supporting early detection of Polycystic Ovary Syndrome (PCOS) and advancing healthcare diagnostics. A huge thank you to my incredible co-author Praveena M for her invaluable contributions to this work, and to my institution Dr. SNS Rajalakshmi College of Arts & Science, Coimbatore for their continued support and encouragement. 🙏 📖 You can read the full paper using this link: 🔗 https://lnkd.in/gFMEFfxM #Research #IEEE #Scopus #ArtificialIntelligence #DeepLearning #PCOS #HealthcareInnovation

Hospital del Mar Hospital del Mar Research Institute An artificial intelligence tool reveals how the brain orients itself in space https://lnkd.in/dbxVDmKX