AIMC Topic: Reproducibility of Results

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Cell Recognition Using BP Neural Network Edge Computing.

Contrast media & molecular imaging
This exploration is to solve the efficiency and accuracy of cell recognition in biological experiments. Neural network technology is applied to the research of cell image recognition. The cell image recognition problem is solved by constructing an im...

Highway Traffic Flow Prediction Model Construction Based on the Gray Theory and BP Neural Network.

Computational intelligence and neuroscience
The short-term traffic flow prediction and modeling of highways are the core content and important foundation of highway management decision-making support systems. It is of great significance to improving the level of highway management. Based on th...

On-Device IoT-Based Predictive Maintenance Analytics Model: Comparing TinyLSTM and TinyModel from Edge Impulse.

Sensors (Basel, Switzerland)
A precise prediction of the health status of industrial equipment is of significant importance to determine its reliability and lifespan. This prediction provides users information that is useful in determining when to service, repair, or replace the...

Comparative evaluation of a prototype deep learning algorithm for autosegmentation of normal tissues in head and neck radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To introduce and validate a newly developed deep-learning (DL) auto-segmentation algorithm for head and neck (HN) organs at risk (OARs) and to compare its performance with a published commercial algorithm.

Robot-assisted ex vivo neobladder reconstruction: preliminary results of surgical skill evaluation.

International journal of computer assisted radiology and surgery
PURPOSE: Advanced developments in the medical field have gradually increased the public demand for surgical skill evaluation. However, this assessment always depends on the direct observation of experienced surgeons, which is time-consuming and varia...

A Machine Learning Approach to Identify Previously Unconsidered Causes for Complications in Aesthetic Breast Augmentation.

Aesthetic plastic surgery
INTRODUCTION: Primary breast augmentation is one of the most commonly requested aesthetic procedures. Considering the large number of procedures performed in connection with a high demand, it is crucial to prevent complications. For this reason, find...

Validity of at-home rapid antigen lateral flow assay and artificial intelligence read to detect SARS-CoV-2.

Diagnostic microbiology and infectious disease
BACKGROUND: The gold standard for COVID-19 diagnosis-reverse-transcriptase polymerase chain reaction (RT-PCR)- is expensive and often slow to yield results whereas lateral flow tests can lack sensitivity.

Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interp...

eICAB: A novel deep learning pipeline for Circle of Willis multiclass segmentation and analysis.

NeuroImage
BACKGROUND: The accurate segmentation, labeling and quantification of cerebral blood vessels on MR imaging is important for basic and clinical research, yet results are not generalizable, and often require user intervention. New methods are needed to...

Deep learning solution for medical image localization and orientation detection.

Medical image analysis
Magnetic Resonance (MR) imaging plays an important role in medical diagnosis and biomedical research. Due to the high in-slice resolution and low through-slice resolution nature of MR imaging, the usefulness of the reconstruction highly depends on th...