Results 211 to 220 of about 189,514 (304)

Where, How, and How Much? A Multicenter Cohort Study of the Relationship Across Lupus Decision‐Aid Modality, Place of Administration, Interruption and Viewing Completeness, and Patient‐Reported Outcomes

Arthritis Care &Research, EarlyView.
Objective We assessed whether shared decision‐making (SDM) and patient acceptability, feasibility, and overall satisfaction with a computerized patient decision aid (PtDA) for patients with systemic lupus erythematosus (SLE) differs by PtDA setting, modality, and the viewing experience. Methods Patients with SLE were invited to view a self‐administered
Jasvinder A. Singh, Mark Beasley, Larry R. Hearld, for the Implementing Decision‐Aid for Lupus in Clinics (IDEAL) Consortium, Winn Chatham, Jasvinder Singh, Sonali Narain, Narender Annapureddy, Diane Kamen, Kimberly Trotter, Vikas Majithia, Cathy Ching, Zineb Aouhab, Swamy Venturupalli, Rosalind Ramsey‐Goldman, Alfred Kim, Maureen McMahon, Sam Lim, Kalpana Bhairavarasu, Alexa Meara, Kenneth Kalunian   +20 more
wiley   +1 more source

Comparison of the accuracy of the image registration methods for the impressions of edentulous jaws. [PDF]

Clin Oral Investig
Liu M, Li X, Qu Z.
europepmc   +1 more source

Fast Diffeomorphic Image Registration using Patch based Fully Convolutional Networks [PDF]

Jiong Wu
openalex   +1 more source

Image Registration on Satellite Images

IOSR Journal of Electronics and Communication Engineering, 2012
openaire   +1 more source

A Scoping Review on Artificial Intelligence–Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases

Arthritis Care &Research, EarlyView.
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah, Alexis Castellanos, Yen Chen, John Piette, Amy Bucher, Susan Murphy   +5 more
wiley   +1 more source

A Physics-Informed Deep Learning Deformable Medical Image Registration Method Based on Neural ODEs. [PDF]

Int J Comput Vis
Amiri-Hezaveh A, Tan S, Deng Q, Umulis D, Cunniff L, Weickenmeier J, Buganza Tepole A.   +6 more
europepmc   +1 more source

Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases With Application to Scleroderma

Arthritis Care &Research, EarlyView.
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim, John Scott, Lauren Fisher, Lauren N. Smith, Willie Stewart, Adrianne Woods, Rob Smithwright, Diane Koher, Parastoo Aslanbeik, Aalok B. Shah, Brad Tibbils, Samantha I. Pitts, Ayse P. Gurses, Yushi Yang, Ana‐Maria Orbai, Antony Rosen, Laura K. Hummers, Scott L. Zeger, Ami A. Shah   +18 more
wiley   +1 more source

Vector field attention for deformable image registration. [PDF]

J Med Imaging (Bellingham)
Liu Y, Chen J, Zuo L, Carass A, Prince JL.   +4 more
europepmc   +1 more source

Registration method for heterogenous remote sensing images with multi-scale and multi-angle

, 2012
Jianwen Ma
openalex   +1 more source