AIMC Topic: Machine Learning

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A Survey on Data-Driven Predictive Maintenance for the Railway Industry.

Sensors (Basel, Switzerland)
In the last few years, many works have addressed Predictive Maintenance (PdM) by the use of Machine Learning (ML) and Deep Learning (DL) solutions, especially the latter. The monitoring and logging of industrial equipment events, like temporal behavi...

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

International journal of molecular sciences
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machin...

Explainable machine-learning predictions for complications after pediatric congenital heart surgery.

Scientific reports
The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of thera...

Review of machine learning methods for RNA secondary structure prediction.

PLoS computational biology
Secondary structure plays an important role in determining the function of noncoding RNAs. Hence, identifying RNA secondary structures is of great value to research. Computational prediction is a mainstream approach for predicting RNA secondary struc...

Characterizing and forecasting the responses of tropical forest leaf phenology to El Nino by machine learning algorithms.

PloS one
Climate change and global warming have serious adverse impacts on tropical forests. In particular, climate change may induce changes in leaf phenology. However, in tropical dry forests where tree diversity is high, species responses to climate change...

A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors.

European radiology
OBJECTIVES: To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based on patient clinical characteristics and conventional radiographs of the lesion.

Automatic annotation of cervical vertebrae in videofluoroscopy images via deep learning.

Medical image analysis
Judging swallowing kinematic impairments via videofluoroscopy represents the gold standard for the detection and evaluation of swallowing disorders. However, the efficiency and accuracy of such a biomechanical kinematic analysis vary significantly am...

Towards personalized nutritional treatment for malnutrition using machine learning-based screening tools.

Clinical nutrition (Edinburgh, Scotland)
Early identification of patients at risk of malnutrition or who are malnourished is crucial in order to start a timely and adequate nutritional therapy. Yet, despite the presence of many nutrition screening tools for use in the hospital setting, ther...

A Knowledge-Based Deep Learning Architecture for Aspect-Based Sentiment Analysis.

International journal of neural systems
The task of sentiment analysis tries to predict the affective state of a document by examining its content and metadata through the application of machine learning techniques. Recent advances in the field consider sentiment to be a multi-dimensional ...

Generation of Chow Parameters and Reduced Variables Through Nearest Neighbor Relations in Threshold Networks.

International journal of neural systems
Generation of useful variables and features is an important issue throughout the machine learning, artificial intelligence, and applied fields for their efficient computations. In this paper, the nearest neighbor relations are proposed for the minima...