. Developing Machine Learning models (N Gorre et al 2023) for clinical applications from scratch can be a cumbersome task requiring varying levels of expertise. Seasoned developers and researchers may also often face incompatible frameworks and data ...
OBJECTIVE: To summarize state-of-the-art artificial intelligence-enabled decision support in surgery and to quantify deficiencies in scientific rigor and reporting.
BACKGROUND: A prognostic assessment method with good sensitivity and specificity plays an important role in the treatment of pancreatic cancer patients. Finding a way to evaluate the prognosis of pancreatic cancer is of great significance for the tre...
Chest radiography is the modality of choice for the identification of rib fractures in young children and there is value for the development of computer-aided rib fracture detection in this age group. However, the automated identification of rib frac...
Computer methods and programs in biomedicine
Mar 5, 2023
BACKGROUND AND OBJECTIVES: Radiomics and deep learning are two popular technologies used to develop computer-aided detection and diagnosis schemes for analysing medical images. This study aimed to compare the effectiveness of radiomics, single-task d...
OBJECTIVE: In this proof-of-concept study, we aimed to develop deep-learning-based classifiers to identify rib fractures on frontal chest radiographs in children under 2 years of age.
We study whether deep neural network based algorithm can filter out mammography phantom images that will pass or fail. With 543 phantom images generated from a mammography unit, we created VGG16 based phantom shape scoring models (multi-and binary-cl...
Diagnosing distal bile duct obstruction remains challenging. This study aimed to examine the diagnostic ability of artificial intelligence (AI) based on clinical biomarkers in diagnosing malignant distal bile duct obstruction. A total of 206 patients...
Computer methods and programs in biomedicine
Feb 21, 2023
BACKGROUND AND OBJECTIVE: Colorectal cancer is a major health concern. It is now the third most common cancer and the fourth leading cause of cancer mortality worldwide. The aim of this study was to evaluate the performance of machine learning algori...
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Feb 20, 2023
PURPOSE: To establish a multilabel-based deep learning (DL) algorithm for automatic detection and categorization of clinically significant peripheral retinal lesions using ultrawide-field fundus images.
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