IEEE Engineering Medicine and Biology Society’s Post

I'm excited to share that my recent research titled "A Comparative Analysis on Detecting Physiological Age of Caenorhabditis Elegans Using Deep Learning Techniques" was published. In this paper, I explore the potential of deep learning for accurately determining the physiological age of C. elegans, a powerful model organism for aging studies. I'm eager to discuss the implications of this research and its potential applications in aging research. Feel free to connect with me to learn more! Paper Link: https://lnkd.in/gj65B2SE GitHub Repository: https://lnkd.in/gdH24_aU #CElegans #DeepLearning #AgingResearch #PhysiologicalAge

One of my coursework projects, "Knee Osteoarthritis Analysis Using Deep Learning and XAI on X-Rays," completed at the Norwegian University of Science and Technology (NTNU), has been published in the IEEE Access Journal. The primary goal of the study was to investigate whether the deep learning models used in this study can classify knee osteoarthritis as accurately as a physician. Many thanks to my supervisor Dr. Ali Shariq Imran. Check it out here: https://lnkd.in/e2pqe--s #IEEE

ALHAMDULILLAH! Excited to share that our paper on "Cervical Spine Fracture Detection and Classification Using a Two-Stage Deep Learning Methodology" has been published in IEEE Access! This research represents a significant step in improving the accuracy and efficiency of diagnosing cervical spine fractures, which is crucial for timely and effective treatment. I am grateful to all the collaborators and supporters who have contributed to this work. Looking forward to the impact this research will have on AI in the medical field. #CervicalSpine #DeepLearning #MachineLearning #ComputerVision #MedicalResearch #PublishedPaper

#AgricultureMdpi – Editor's Choice Article 🔺 Impacts of Background Removal on Convolutional Neural Networks for Plant Disease Classification In-Situ ✍️ by Kamal KC et al. 🖱️ Click to read the full article: https://lnkd.in/gjxNjrXA #segmentation #backgroundsubtraction #transferlearning #deepconvolutionalneuralnetwork #plantdiseaseimageclassification

🍅🔬 Delighted to share my latest paper, "Efficient Diagnosis of Bacterial Leaf Spot in Tomato Plants using Deep Learning CNN Models," published in Plant Bulletin Journal! 🌱💡 Our research explores cutting-edge applications of Convolutional Neural Networks for swift and accurate detection of plant diseases. Exciting strides in agrotech! 🌿🚀 Check out the paper here: [https://lnkd.in/dFHE69hY] #PlantPathology #DeepLearning #AgTech #ResearchInnovation 📚🌐#PlantScience #DeepLearning #Research #TeamWork 🙏

Hi connections, it gives me immense pleasure to share that our research paper "Early detection of Alzheimer's Disease using Deep Learning" has been published at International Journal of Scientific Research In Engineering & Management (IJSREM), 2024, Volume 8, Issue 05, ISSN No. 2582-3930, in month of May. In this paper, we've proposed a hybridized Deep Learning model which is a combination of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Deep Belief Network (DBN) algorithms which makes a significant impact in healthcare as well as in the early diagnosis of Alzheimer's Disease. #researchpaper #IJSREM #CNN #LSTM #DBN #Deeplearning #hybridizeddeeplearningmodel

Read #NewPaper “Assessing Cardiac Functions of Zebrafish from Echocardiography Using Deep Learning” by Mao-Hsiang Huang et al. See more details at: https://lnkd.in/gQy4b_Wd #deeplearning #heartdisease

That's a wrap. The Modeling Randomness in Neural Network Training Workshop was a big success due to both the speakers as well as the participants (many of whom presented posters). I can't wait to see where it all goes from here from collaborations to future conferences to groundbreaking results. For a short time at least, I will be a spectator as I have accepted a new role and will be taking a hiatus from research. This is both exciting and terrifying as I have never worked outside of scientific research. What a way to wrap up my time working in Foundational AI at PNNL. More to come.

Hi connections, it gives me immense pleasure to share that our research paper "Early detection of Alzheimer's Disease using Deep Learning" has been published at International Journal of Scientific Research In Engineering & Management (IJSREM), 2024, Volume 8, Issue 05, ISSN No. 2582-3930, in month of May. In this paper, we've proposed a hybridized Deep Learning model which is a combination of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Deep Belief Network (DBN) algorithms which makes a significant impact in healthcare as well as in the early diagnosis of Alzheimer’s Disease. IJSREM #researchpaper #IJSREM #CNN #LSTM #DBN #Deeplearning #hybridizeddeeplearningmodel