AIMC Topic: Reproducibility of Results

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Using Machine Learning to Develop a Short-Form Measure Assessing 5 Functions in Patients With Stroke.

Archives of physical medicine and rehabilitation
OBJECTIVE: This study aimed to develop and validate a machine learning-based short measure to assess 5 functions (the ML-5F) (activities of daily living [ADL], balance, upper extremity [UE] and lower extremity [LE] motor function, and mobility) in pa...

Evolved explainable classifications for lymph node metastases.

Neural networks : the official journal of the International Neural Network Society
A novel evolutionary approach for Explainable Artificial Intelligence is presented: the "Evolved Explanations" model (EvEx). This methodology combines Local Interpretable Model Agnostic Explanations (LIME) with Multi-Objective Genetic Algorithms to a...

Using Deep Learning to Automate the Detection of Flaws in Nuclear Fuel Channel UT Scans.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nuclear reactor inspections are critical to ensure the safety and reliability of a nuclear facility's operation. In Canada, ultrasonic testing (UT) is used to inspect the health of pressure tubes that are part of Canada's Deuterium Uranium (CANDU) re...

Application of Reinforcement Learning and Deep Learning in Multiple-Input and Multiple-Output (MIMO) Systems.

Sensors (Basel, Switzerland)
The current wireless communication infrastructure has to face exponential development in mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems and their variants (i.e., Multi-User MIMO and Massive MIMO) are the...

Anomaly Detection in Asset Degradation Process Using Variational Autoencoder and Explanations.

Sensors (Basel, Switzerland)
Development of predictive maintenance (PdM) solutions is one of the key aspects of Industry 4.0. In recent years, more attention has been paid to data-driven techniques, which use machine learning to monitor the health of an industrial asset. The maj...

Selective prediction-set models with coverage rate guarantees.

Biometrics
The current approach to using machine learning (ML) algorithms in healthcare is to either require clinician oversight for every use case or use their predictions without any human oversight. We explore a middle ground that lets ML algorithms abstain ...

Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

Veterinary pathology
The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or cl...

Evaluation of Machine Learning Methods for Monitoring the Health of Guyed Towers.

Sensors (Basel, Switzerland)
This paper presents the development of a methodology to detect and evaluate faults in cable-stayed towers, which are part of the infrastructure of Brazil's interconnected electrical system. The proposed method increases system reliability and minimiz...

Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.

The Journal of pathology
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...