AIMC Topic: Reproducibility of Results

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Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit.

Scientific reports
Acute gastrointestinal bleeding is the most common gastrointestinal cause for hospitalization. For high-risk patients requiring intensive care unit stay, predicting transfusion needs during the first 24 h using dynamic risk assessment may improve res...

Heterogeneous bi-directional recurrent neural network combining fusion health indicator for predictive analytics of rotating machinery.

ISA transactions
Data-driven intelligent methods arise the increasing demand for predictive analytics to evaluate the operational reliability and natural degradation of rotating machinery. Nevertheless, accurate and timely predictive analytics is still regarded as an...

Towards markerless surgical tool and hand pose estimation.

International journal of computer assisted radiology and surgery
PURPOSE:  : Tracking of tools and surgical activity is becoming more and more important in the context of computer assisted surgery. In this work, we present a data generation framework, dataset and baseline methods to facilitate further research in ...

Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model.

Drug metabolism and pharmacokinetics
We constructed machine learning-based pharmacokinetic prediction models with very high performance. The models were trained on 26138 and 16613 compounds involved in metabolic stability and cytochrome P450 inhibition, respectively. Because the compoun...

Integrated Analytical Framework for the Development of Artificial Intelligence-Based Medical Devices.

Therapeutic innovation & regulatory science
INTRODUCTION: A persistent fundamental problem in applying artificial intelligence (AI) to medical devices is achieving high performance while guaranteeing the safety and reliability of AI solutions. However, the regulation of medical devices and tha...

Alberta Stroke Program Early CT Score Calculation Using the Deep Learning-Based Brain Hemisphere Comparison Algorithm.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a promising tool for the evaluation of stroke expansion to determine suitability for reperfusion therapy. The aim of this study was to validate deep learning-based AS...

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system.

Journal of biomechanics
Spatiotemporal parameters can characterize the gait patterns of individuals, allowing assessment of their health status and detection of clinically meaningful changes in their gait. Video-based markerless motion capture is a user-friendly, inexpensiv...

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models.

International journal of computer assisted radiology and surgery
PURPOSE: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and surgery planning of pelvic bone diseases. Existing methods for pelvic bone segmentation are either hand-crafted or semi-automatic and achieve limited ...