Journal of imaging informatics in medicine
Apr 18, 2024
While dual-energy computed tomography (DECT) technology introduces energy-specific information in clinical practice, single-energy CT (SECT) is predominantly used, limiting the number of people who can benefit from DECT. This study proposed a novel m...
Journal of imaging informatics in medicine
Apr 18, 2024
We aimed to develop and validate a deep convolutional neural network (DCNN) model capable of accurately identifying spondylolysis or spondylolisthesis on lateral or dynamic X-ray images. A total of 2449 lumbar lateral and dynamic X-ray images were co...
OBJECTIVES: To develop and validate an artificial intelligence (AI) system for measuring and detecting signs of carpal instability on conventional radiographs.
OBJECTIVES: To distinguish histological subtypes of renal tumors using radiomic features and machine learning (ML) based on multiphase computed tomography (CT).
OBJECTIVE: Here we trained an automatic phenotype assessment tool to recognize syndromic ears in two syndromes in fetuses-=CHARGE and Mandibulo-Facial Dysostosis Guion Almeida type (MFDGA)-versus controls.
Forensic science, medicine, and pathology
Apr 18, 2024
The study investigated the relationship between the histological compositions of the tricuspid, pulmonary, mitral, and aortic valves, and age. All 85 fresh human hearts were obtained with an age range between 20 and 90 years. The central area of the ...
The Journal of laryngology and otology
Apr 18, 2024
OBJECTIVES: Clinician acceptance influences technology adoption, but UK health professionals' attitudes towards artificial intelligence (AI) in hearing healthcare are unclear. This study aimed to address this knowledge gap.
Medical & biological engineering & computing
Apr 18, 2024
Imagined speech recognition has developed as a significant topic of research in the field of brain-computer interfaces. This innovative technique has great promise as a communication tool, providing essential help to those with impairments. An imagin...
OBJECTIVE: The feasibility of using deep learning in ultrasound imaging to predict the ambulatory status of patients with Duchenne muscular dystrophy (DMD) was previously explored for the first time. The present study further used clustering algorith...
BACKGROUND AND OBJECTIVES: Personalized donation strategies based on haemoglobin (Hb) prediction models may reduce Hb deferrals and hence costs of donation, meanwhile improving commitment of donors. We previously found that prediction models perform ...
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