AIMC Topic: Machine Learning

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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...

Optical coherence tomography for identification of malignant pulmonary nodules based on random forest machine learning algorithm.

PloS one
OBJECTIVE: To explore the feasibility of using random forest (RF) machine learning algorithm in assessing normal and malignant peripheral pulmonary nodules based on in vivo endobronchial optical coherence tomography (EB-OCT).

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 ...

Machine learning and natural language processing to identify falls in electronic patient care records from ambulance attendances.

Informatics for health & social care
We derived machine learning models utilizing features generated by natural language processing (NLP) of free-text data from an ambulance services provider to identify fall cases. The data comprised samples of electronic patient care records care reco...

A systematic review of robotic surgery: From supervised paradigms to fully autonomous robotic approaches.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: From traditional open surgery to laparoscopic surgery and robot-assisted surgery, advances in robotics, machine learning, and imaging are pushing the surgical approach to-wards better clinical outcomes. Pre-clinical and clinical evidence ...

Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Environmental science & technology
Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimenta...

Deep learning for retention time prediction in reversed-phase liquid chromatography.

Journal of chromatography. A
Retention time prediction in high-performance liquid chromatography (HPLC) is the subject of many studies since it can improve the identification of unknown molecules in untargeted profiling using HPLC coupled with high-resolution mass spectrometry. ...

On the Performance of Generative Adversarial Network by Limiting Mode Collapse for Malware Detection Systems.

Sensors (Basel, Switzerland)
Generative adversarial network (GAN) has been regarded as a promising solution to many machine learning problems, and it comprises of a generator and discriminator, determining patterns and anomalies in the input data. However, GANs have several comm...

Machine learning approaches for the prediction of postoperative complication risk in liver resection patients.

BMC medical informatics and decision making
BACKGROUND: For liver cancer patients, the occurrence of postoperative complications increases the difficulty of perioperative nursing, prolongs the hospitalization time of patients, and leads to large increases in hospitalization costs. The ability ...