OBJECTIVES: To investigate the usefulness of machine learning (ML) models using pretreatment F-FDG-PET-based radiomic features for predicting adverse clinical events (ACEs) in patients with cardiac sarcoidosis (CS).
PURPOSE: To investigate attitudes and perspectives on the use of artificial intelligence (AI) in the assessment of screening mammograms among women invited to BreastScreen Norway.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 16, 2024
Liver vessel segmentation in magnetic resonance imaging data is important for the computational analysis of vascular remodeling, associated with a wide spectrum of diffuse liver diseases. Existing approaches rely on contrast enhanced imaging data, bu...
OBJECTIVE: Identifying participants who will progress to advanced stage in knee osteoarthritis (KOA) trials remains a significant challenge. Current tools, relying on total knee replacements (TKR), fall short in reliability due to the extraneous fact...
The American journal of emergency medicine
Mar 16, 2024
OBJECTIVE: To develop and externally validate models based on neural networks and natural language processing (NLP) to identify suspected serious infections in emergency department (ED) patients afebrile at initial presentation.
OBJECTIVE: Deep learning algorithms have commonly been used for the differential diagnosis between benign and malignant thyroid nodules. The aim of the study described here was to develop an integrated system that combines a deep learning model and a...
BACKGROUND: Accurately predicting survival in patients with cancer is crucial for both clinical decision-making and patient counseling. The primary aim of this study was to generate the first machine-learning algorithm to predict the risk of mortalit...
Protein-DNA and protein-RNA interactions are involved in many biological processes and regulate many cellular functions. Moreover, they are related to many human diseases. To understand the molecular mechanism of protein-DNA binding and protein-RNA b...
Alzheimer's disease (AD) is the general form of dementia, leading to a progressive neurological disorder characterized by memory loss due to brain cell damage. Artificial Intelligence (AI) assists in the early identification and prediction of AD pati...
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a challenging task due to nuclei variances in staining and size, overlapp...
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