Results 191 to 200 of about 3,519,655 (320)

Isolated subdural hematomas in mild traumatic brain injury. Part 1: the association between radiographic characteristics and neurosurgical intervention [PDF]

, 2018
Alessandro Orlando, A. Stewart Levy, B. A. Rubin, Allen Tanner, Matthew M. Carrick, Mark J. Lieser, David Hamilton, Charles W. Mains, David Bar‐Or   +8 more
openalex   +1 more source

Derivation and validation of the Pediatric Community‐Acquired Pneumonia Severity (PedCAPS) score: A prospective cohort study

Journal of Hospital Medicine, EarlyView.
Abstract Introduction Community‐acquired pneumonia (CAP) is a frequent and costly cause of pediatric emergency department (ED) visits and hospitalizations. Previous prognostic tools for CAP are limited by small samples, single‐center or retrospective designs, lack of generalizability to ED settings, lack of biomarkers, or limited objective data.
Todd A. Florin, Ron Reeder, Lilliam Ambroggio, Richard M. Ruddy, Samir S. Shah, Allison Cator, Matthew J. Lipshaw, Geoffrey A. Capraro, Laura F. Sartori, Amy Y. Cheng, Leah Tzimenatos, Patrick S. Walsh, Claudia R. Morris, Chris A. Rees, Son H. McLaren, Tamar R. Lubell, Chari D. Larsen, Justin Moher, Eileen J. Klein, Shubhada Hooli, Nathan Kuppermann, Pediatric Emergency Care Applied Research Network (PECARN) PedCAPS Investigators   +21 more
wiley   +1 more source

The potential use of scout views as an adjunct tool in CT-guided intervention. [PDF]

Sci Rep
Conroy D, Werncke T, Waldeck S, Wacker F, von Falck C.   +4 more
europepmc   +1 more source

Clinical and radiographic outcomes of meniscus surgery and future targets for biologic intervention: A review of data from the MOON Group

, 2017
Robert W. Westermann, Morgan H. Jones, David Wasserstein, Kurt P. Spindler   +3 more
openalex   +1 more source

Analysis of Upper Airway Morphology Using Four‐Dimensional Dynamic MRI With Active Deep Learning‐Based Automatic Segmentation

Journal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Background Upper‐airway morphology changes during breathing can be captured with cine 4D MRI. Active‐learning nnU‐Net reduces manual labeling while maintaining accuracy. Purpose For automatic upper airway segmentation on free‐breathing cine 4D MRI using active learning and quantifying dynamic changes under two mouth positions.
Cheng‐Yang Yu, Meng‐Chen Chung, Yunn‐Jy Chen, Han‐Wei Wang, Jonathan X. Zhou, Shih‐Lung Chen, Kevin T. Chen, Tiffany Ting‐Fang Shih   +7 more
wiley   +1 more source

A distinct radiologic perspective on parotid pleomorphic adenoma: sialo-CBCT case report. [PDF]

BMC Oral Health
Çağlayan F, Sümbüllü MA, Şahin A, Ağirman KT.   +3 more
europepmc   +1 more source

Analysis of Pulsatile Vessel Expansion in Healthy, COPD‐and PH‐Patients Using Dynamic Vessel Segmentation in Free‐Breathing Lung MRI

Journal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Background The pulsatile expansion of pulmonary vessels carries dynamic cardiopulmonary information that may reveal disease earlier than structural changes alone. Purpose To test (i) intra‐ and inter‐scan repeatability of dynamic vessel metrics in healthy subjects, and (ii) whether chronic obstructive pulmonary disease (COPD) and postcapillary
Julian Glandorf, Marius M. Klein, Filip Klimeš, Agilo Luitger Kern, Marcel Gutberlet, Jens M. Hohlfeld, Marius M. Hoeper, Karen M. Olsson, Frank Wacker, Jens Vogel‐Claussen, Andreas Voskrebenzev   +10 more
wiley   +1 more source

An evaluation of approaches to imaging for the pre-surgical assessment of intraocular foreign body size. [PDF]

Br J Ophthalmol
Wanniarachchi K, Kaza H, Safi A, Ratneswaren T, Poulson A, Snead MP.   +5 more
europepmc   +1 more source

The skeletal phenotype of intermediate GM1 gangliosidosis: Clinical, radiographic and densitometric features, and implications for clinical monitoring and intervention

, 2019
Carlos R. Ferreira, Debra S. Regier, Robin Yoon, Kristen S. Pan, Jean M. Johnston, Sandra Yang, Jürgen W. Spranger, Cynthia J. Tifft   +7 more
openalex   +2 more sources

Using Convolutional Neural Networks for the Classification of Suboptimal Chest Radiographs

Journal of Medical Radiation Sciences, EarlyView.
This study evaluated DenseNet121 and YOLOv8 neural networks in detecting suboptimal chest x‐rays for quality control. Through training, validation, and testing, both AI models effectively classified chest X‐ray quality, highlighting the potential to provide radiographers with feedback to enhance image quality.
Emily Huanke Liu, Daniel Carrion, Mohamed Khaldoun Badawy   +2 more
wiley   +1 more source