Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Digital analysis of the relationship between maximum bite force and 3-dimensional arrangement of mandibular first molars.
J Clin Exp Dent
December 2024
Doctor, Lecturer. Faculty of Odonto-Stomatology, University of Medicine and Pharmacy at Ho Chi Minh City, 652 Nguyen Trai Street, Ward 11, District 5, 749000, Ho Chi Minh City, Vietnam.
Background: Bite force is one of the important factors that determine the chewing efficiency of molars. This study aimed to investigate the relationship of the maximum bite force (MBF) to the 3-dimensional (3D) arrangement of the first mandibular molars in Angle's class I healthy adults using a digital protocol.
Material And Methods: Subjects were 33 adults (16 males and 17 females) aged 18-25, with Angle's class I occlusions and healthy dentitions.
Tsunami modelling over global oceans.
R Soc Open Sci
January 2025
National Centre for Coastal Research (NCCR), Ministry of Earth Sciences (MoES), Chennai, India.
Tsunamis are massive waves generated by sudden water displacement on the ocean surface, causing devastation as they sweep across the coastlines, posing a global threat. The aftermath of the 2004 Indian Ocean tsunami led to the establishment of the Indian Tsunami Early Warning System (ITEWS). Predicting real-time tsunami heights and the resulting coastal inundation is crucial in ITEWS to safeguard the coastal communities.
View Article and Find Full Text PDFCXR-LLaVA: a multimodal large language model for interpreting chest X-ray images.
Eur Radiol
January 2025
Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.
Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.
Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.
BMC Med Imaging
January 2025
Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Background: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality.
View Article and Find Full Text PDFData-Driven Improvement of Local Hybrid Functionals: Neural-Network-Based Local Mixing Functions and Power-Series Correlation Functionals.
J Chem Theory Comput
January 2025
Technische Universitát Berlin, Institut für Chemie, Theoretische Chemie/Quantenchemie, Sekr. C7, Straße des 17. Juni 135, Berlin D-10623, Germany.
Local hybrid functionals (LHs) use a real-space position-dependent admixture of exact exchange (EXX), governed by a local mixing function (LMF). The systematic construction of LMFs has been hampered over the years by a lack of exact physical constraints on their valence behavior. Here, we exploit a data-driven approach and train a new type of "n-LMF" as a relatively shallow neural network.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!