AIMC Topic: Prospective Studies
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Machine learning decision support model for discharge planning in stroke patients.
Journal of clinical nursing
Feb 15, 2024
BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, ...
Low-tube-voltage whole-body CT angiography with extremely low iodine dose: a comparison between hybrid-iterative reconstruction and deep-learning image-reconstruction algorithms.
Clinical radiology
Feb 15, 2024
AIM: To evaluate arterial enhancement, its depiction, and image quality in low-tube potential whole-body computed tomography (CT) angiography (CTA) with extremely low iodine dose and compare the results with those obtained by hybrid-iterative reconst...
Machine learning clustering of adult spinal deformity patients identifies four prognostic phenotypes: a multicenter prospective cohort analysis with single surgeon external validation.
The spine journal : official journal of the North American Spine Society
Feb 15, 2024
BACKGROUND CONTEXT: Among adult spinal deformity (ASD) patients, heterogeneity in patient pathology, surgical expectations, baseline impairments, and frailty complicates comparisons in clinical outcomes and research. This study aims to qualitatively ...
A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray.
Nature communications
Feb 14, 2024
Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based o...
Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.
Journal of computer assisted tomography
Feb 12, 2024
OBJECTIVE: The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance angiography (MRA) at 3 T.
Acute Kidney Injury in Acute Myocardial Infarction and Its Outcome at 3 and 6 Months.
Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Feb 12, 2024
Epidemiological data on the prevalence of acute kidney injury (AKI) in acute coronary syndrome are sparse, with most studies having been conducted retrospectively. This study prospectively analyzed the incidence of AKI in patients with acute myocardi...
Artificial intelligence technology improves the accuracy of preoperative planning in primary total hip arthroplasty.
Asian journal of surgery
Feb 10, 2024
OBJECTIVE: Successful total hip arthroplasty relies on accurate preoperative planning. However, the conventional preoperative planning, a two-dimensional method using X-ray template, has shown poor reliability of predicting component size. To our kno...
Prospective Comparison of Free-Breathing Accelerated Cine Deep Learning Reconstruction Versus Standard Breath-Hold Cardiac MRI Sequences in Patients With Ischemic Heart Disease.
AJR. American journal of roentgenology
Feb 7, 2024
Cine cardiac MRI sequences require repeated breath-holds, which can be difficult for patients with ischemic heart disease (IHD). The purpose of the study was to compare a free-breathing accelerated cine sequence using deep learning (DL) reconstruct...
AI-based diagnosis and phenotype - Genotype correlations in syndromic craniosynostoses.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Feb 5, 2024
Apert (AS), Crouzon (CS), Muenke (MS), Pfeiffer (PS), and Saethre Chotzen (SCS) are among the most frequently diagnosed syndromic craniosynostoses. The aims of this study were (1) to train an innovative model using artificial intelligence (AI)-based ...
Combining Transcranial Direct Current Stimulation With Hand Robotic Rehabilitation in Chronic Stroke Patients: A Double-Blind Randomized Clinical Trial.
American journal of physical medicine & rehabilitation
Feb 5, 2024
OBJECTIVE: This study aimed to assess the impact of combining transcranial direct current stimulation with end-effector robot-assisted treatment on upper limb function, spasticity, and hand dexterity in chronic stroke patients.
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