AIMC Topic: Algorithms

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Automation of penicillin adverse drug reaction categorisation and risk stratification with machine learning natural language processing.

International journal of medical informatics
BACKGROUND: The penicillin adverse drug reaction (ADR) label is common in electronic health records (EHRs). However, there is significant misclassification between allergy and intolerance within the EHR and most patients can be delabelled after an im...

AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs.

Physical and engineering sciences in medicine
According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impact. The main challenge in fighting against this disease is its scale. Due to the outbreak, medical f...

Framework for classification of cancer gene expression data using Bayesian hyper-parameter optimization.

Medical & biological engineering & computing
Computational classification of cancers is an important research problem. Gene expression data has 1000s of features, very few samples, and a class imbalance problem. In this paper, we have proposed a framework for the classification of cancer gene e...

Path Driven Dual Arm Mobile Co-Manipulation Architecture for Large Part Manipulation in Industrial Environments.

Sensors (Basel, Switzerland)
Collaborative part transportation is an interesting application as many industrial sectors require moving large parts among different areas of the workshops, using a large amount of the workforce on this tasks. Even so, the implementation of such kin...

Bayesian supervised machine learning classification of neural networks with pathological perturbations.

Biomedical physics & engineering express
Extraction of temporal features of neuronal activity from electrophysiological data can be used for accurate classification of neural networks in healthy and pathologically perturbed conditions. In this study, we provide an extensive approach for the...

PM₂.₅ Monitoring: Use Information Abundance Measurement and Wide and Deep Learning.

IEEE transactions on neural networks and learning systems
This article devises a photograph-based monitoring model to estimate the real-time PM concentrations, overcoming currently popular electrochemical sensor-based PM monitoring methods' shortcomings such as low-density spatial distribution and time dela...

Multi-Source Transfer Learning Via Multi-Kernel Support Vector Machine Plus for B-Mode Ultrasound-Based Computer-Aided Diagnosis of Liver Cancers.

IEEE journal of biomedical and health informatics
B-mode ultrasound (BUS) imaging is a routine tool for diagnosis of liver cancers, while contrast-enhanced ultrasound (CEUS) provides additional information to BUS on the local tissue vascularization and perfusion to promote diagnostic accuracy. In th...

ML-Net: Multi-Channel Lightweight Network for Detecting Myocardial Infarction.

IEEE journal of biomedical and health informatics
Due to the complexity of myocardial infarction (MI) waveform, most traditional automatic diagnosis models rarely detect it, while those able to detect MI often require high computing and storage capacity, rendering them unsuitable for portable device...

Natural Language Mapping of Electrocardiogram Interpretations to a Standardized Ontology.

Methods of information in medicine
BACKGROUND: Interpretations of the electrocardiogram (ECG) are often prepared using software outside the electronic health record (EHR) and imported via an interface as a narrative note. Thus, natural language processing is required to create a compu...

A Two-Phase Mitosis Detection Approach Based on U-Shaped Network.

BioMed research international
This paper proposes a deep learning-based method for mitosis detection in breast histopathology images. A main problem in mitosis detection is that most of the datasets only have weak labels, i.e., only the coordinates indicating the center of the mi...