AIMC Topic: Humans

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Development of retake support system for lateral knee radiographs by using deep convolutional neural network.

Radiography (London, England : 1995)
INTRODUCTION: Lateral radiography of the knee joint is frequently performed; however, the retake rate is high owing to positioning errors. Therefore, in this study, to reduce the required number and time of image retakes, we developed a system that c...

Natural language processing for the surveillance of postoperative venous thromboembolism.

Surgery
BACKGROUND: The objective of this study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes.

Computational representations of protein-ligand interfaces for structure-based virtual screening.

Expert opinion on drug discovery
: Structure-based virtual screening (SBVS) is an essential strategy for hit identification. SBVS primarily uses molecular docking, which exploits the protein-ligand binding mode and associated affinity score for compound ranking. Previous studies hav...

On the Ethics and Practicalities of Artificial Intelligence, Risk Assessment, and Race.

The journal of the American Academy of Psychiatry and the Law
Artificial intelligence (AI) has been put forth as a potential means of improving and expediting violence risk assessment in forensic psychiatry. Furthermore, it has been proffered as a means of mitigating bias by replacing subjective human judgement...

Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study.

Computers in biology and medicine
The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is a significant reason of ED crowding in hospitals worldwide. Timely forecast of patients arriving at ED can help the hospital management in early planning and ...

SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation.

Medical image analysis
Semi-Supervised classification and segmentation methods have been widely investigated in medical image analysis. Both approaches can improve the performance of fully-supervised methods with additional unlabeled data. However, as a fundamental task, s...

Image texture, low contrast liver lesion detectability and impact on dose: Deep learning algorithm compared to partial model-based iterative reconstruction.

European journal of radiology
OBJECTIVES: To compare deep learning (True Fidelity, TF) and partial model based Iterative Reconstruction (ASiR-V) algorithm for image texture, low contrast lesion detectability and potential dose reduction.

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Computers in biology and medicine
Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premature babies cared for in neonatal intensive care units (NICUs). Mortality risk prediction in this setting can greatly improve patient outcomes and reso...