AIMC Topic: Reproducibility of Results

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Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Evaluating lower extremity alignment using full-leg plain radiographs is an essential step in diagnosis and treatment of patients with knee osteoarthritis. The study objective was to present a deep learning-based anatomical landmark recognit...

[Artificial intelligence and radiomics : Value in cardiac MRI].

Radiologie (Heidelberg, Germany)
CLINICAL/METHODICAL ISSUE: Cardiac diseases are the leading cause of death. Many diseases can be specifically treated once a valid diagnosis is established. Cardiac magnetic resonance imaging (MRI) plays a central role in the workup of many cardiac p...

Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is rapidly expanding in medicine despite a lack of consensus on its application and evaluation.

Link Quality Estimation for Wireless ANDON Towers Based on Deep Learning Models.

Sensors (Basel, Switzerland)
Data reliability is of paramount importance for decision-making processes in the industry, and for this, having quality links for wireless sensor networks plays a vital role. Process and machine monitoring can be carried out through ANDON towers with...

Anomaly Detection in Satellite Telemetry Data Using a Sparse Feature-Based Method.

Sensors (Basel, Switzerland)
Anomaly detection based on telemetry data is a major issue in satellite health monitoring which can identify unusual or unexpected events, helping to avoid serious accidents and ensure the safety and reliability of operations. In recent years, sparse...

An Improved Load Forecasting Method Based on the Transfer Learning Structure under Cyber-Threat Condition.

Computational intelligence and neuroscience
Smart grid is regarded as an evolutionary regime of existing power grids. It integrates artificial intelligence and communication technologies to fundamentally improve the efficiency and reliability of power systems. One serious challenge for the sma...

Development and validation of a deep learning-based protein electrophoresis classification algorithm.

PloS one
BACKGROUND: Protein electrophoresis (PEP) is an important tool in supporting the analytical characterization of protein status in diseases related to monoclonal components, inflammation, and antibody deficiency. Here, we developed a deep learning-bas...

Uncovering additional predictors of urothelial carcinoma from voided urothelial cell clusters through a deep learning-based image preprocessing technique.

Cancer cytopathology
BACKGROUND: Urine cytology is commonly used as a screening test for high-grade urothelial carcinoma for patients with risk factors or hematuria and is an essential step in longitudinal monitoring of patients with previous bladder cancer history. Howe...

Integration of reference data from different Rapid-E devices supports automatic pollen detection in more locations.

The Science of the total environment
Pollen is the most common cause of seasonal allergies, affecting over 33 % of the European population, even when considering only grasses. Informing the population and clinicians in real-time about the actual presence of pollen in the atmosphere is e...