Machine learning
Researchers from Shenyang University of Technology have proposed a novel fault identification method based on variable pooling multiscale CNN (VPMCNN) to solve the bearing industrial problem of huge variable features and inherent multiscale characteristics in acoustic emission (AE) signals. The method involves obtaining pooling projection components (PPCs) through the variable
Machine learning
Researchers from Marmara University have developed a computer-based diagnostic software that uses deep learning techniques to assess the segmentation of the mandibular condyle in ultrasound images. This innovative approach has demonstrated high accuracy, with an F1 score of 0.93, sensitivity of 0.90, and precision of 0.96. The
Machine learning
Researchers from Shenyang Ligong University have made a groundbreaking discovery in the field of machine learning, proposing a novel framework called the Multi-Scale Diffusion Transformer (MSDT) for multimodal image fusion. MSDT seamlessly combines a latent diffusion model with a transformer-based architecture to address the challenges of inadequate feature representation, limited
Machine learning
Research findings on Machine Learning - Computational Intelligence have shed light on a new active learning framework that optimizes the utilization of annotation resources in medical image segmentation and classification tasks. This framework, proposed by researchers at the College of Physics and Information Engineering, aims to reduce annotation costs by
Machine learning
Researchers at the Affiliated People's Hospital of Jiangsu University in China have made a significant breakthrough in understanding the molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) and Hodgkin lymphoma (HL). By combining bioinformatics and machine learning techniques, the team identified 150 shared genes at the
Machine learning
A groundbreaking study published in the journal Scientific Reports has shed light on the complex relationship between periodontitis (PD) and systemic lupus erythematosus (SLE). Researchers at the First Affiliated Hospital of Xinjiang Medical University employed multi-omics methodologies to analyze expression datasets from the Gene Expression Omnibus (GEO) database, identifying 32
Machine learning
Pursuing a career in fields like Artificial Intelligence, Architecture, Human Resource Management, and Clinical Psychology requires guidance from experts. Renowned educationist Syed Azhar Husnain Abidi offers valuable advice on suitable degrees, top universities, and key areas of focus for students in Pakistan. From developing programming skills to understanding labor laws,
Machine learning
A new study on neural computation has made a breakthrough in sentiment analysis using a proposed framework that combines deep learning and heuristic methods. The research, conducted by the Department of Computer Science and Engineering at RMK College of Engineering and Technology in Thiruvallur, India, aimed to overcome the limitations
Machine learning
A recent study published in the European Journal On Artificial Intelligence suggests that machine learning fairness enhancement methods based on data bias correction can be improved by exploring sensitive attributes directly from data itself. The research, conducted by investigators from the School of Computer Science and Technology, Tianjin, China, proposes
Machine learning
Researchers at the University of Alberta have successfully developed an artificial intelligence system to detect camera rotation in minimally invasive surgery (MIS) procedures, mitigating the difficulty and cognitive load on surgeons. This innovative approach leverages a convolutional neural network (CNN) to automatically correct camera rotation issues during MIS procedures. The
Machine learning
Malla Reddy University (MRU) in Hyderabad, India, has made a significant commitment to incorporating Artificial Intelligence (AI) and Machine Learning (ML) into its engineering programs, recognizing the growing demand for AI-skilled professionals in India and globally. With a strategic focus on equipping students with cutting-edge knowledge and practical experience, MRU
Machine learning
Researchers at the University of New South Wales have found that integrating Explainable Artificial Intelligence (XAI) with machine learning (ML) algorithms significantly improves clinician trust in ML-driven decisions for glaucoma detection. By providing a deeper understanding of the logic and reasoning behind ML algorithms, XAI techniques enhance the transparency and
