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ElectroPredictor: An Application to Predict Mayr's Electrophilicity through Implementation of an Ensemble Model Based on Machine Learning Algorithms.

Journal of chemical information and modeling
Electrophilicity () is one of the most important parameters to understand the reactivity of an organic molecule. Although the theoretical electrophilicity index (ω) has been associated with in a small homologous series, the use of to predict in a ...

Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets.

Sensors (Basel, Switzerland)
Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. ...

Multiple machine learning methods aided virtual screening of Na 1.5 inhibitors.

Journal of cellular and molecular medicine
Na 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion chan...

Reinforcement learning using Deep networks and learning accurately localizes brain tumors on MRI with very small training sets.

BMC medical imaging
BACKGROUND: Supervised deep learning in radiology suffers from notorious inherent limitations: 1) It requires large, hand-annotated data sets; (2) It is non-generalizable; and (3) It lacks explainability and intuition. It has recently been proposed t...

A System for Converting and Recovering Texts Managed as Structured Information.

Scientific reports
This paper introduces a system that incorporates several strategies based on scientific models of how the brain records and recovers memories. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architectu...

Klarigi: Characteristic explanations for semantic biomedical data.

Computers in biology and medicine
Annotation of biomedical entities with ontology classes provides for formal semantic analysis and mobilisation of background knowledge in determining their relationships. To date, enrichment analysis has been routinely employed to identify classes th...

Querying semantic catalogues of biomedical databases.

Journal of biomedical informatics
BACKGROUND: Secondary use of health data is a valuable source of knowledge that boosts observational studies, leading to important discoveries in the medical and biomedical sciences. The fundamental guiding principle for performing a successful obser...

Transforming epilepsy research: A systematic review on natural language processing applications.

Epilepsia
Despite improved ancillary investigations in epilepsy care, patients' narratives remain indispensable for diagnosing and treatment monitoring. This wealth of information is typically stored in electronic health records and accumulated in medical jour...

Medical Image Classification Based on Semi-Supervised Generative Adversarial Network and Pseudo-Labelling.

Sensors (Basel, Switzerland)
Deep learning has substantially improved the state-of-the-art in object detection and image classification. Deep learning usually requires large-scale labelled datasets to train the models; however, due to the restrictions in medical data sharing and...

An open-access breast lesion ultrasound image database‏: Applicable in artificial intelligence studies.

Computers in biology and medicine
Breast cancer is one of the largest single contributors to the burden of disease worldwide. Early detection of breast cancer has been shown to be associated with better overall clinical outcomes. Ultrasonography is a vital imaging modality in managin...