AIMC Topic: Data Mining

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Multi-Class Neural Networks to Predict Lung Cancer.

Journal of medical systems
Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of the patient records can help in diagnosing cancer during Stage 1. Usi...

Ontology-based specification and generation of search queries for post-market surveillance.

Journal of biomedical semantics
BACKGROUND: The vigilant observation of medical devices during post-market surveillance (PMS) for identifying safety-relevant incidents is a non-trivial task. A wide range of sources has to be monitored in order to integrate all accessible data about...

CollaboNet: collaboration of deep neural networks for biomedical named entity recognition.

BMC bioinformatics
BACKGROUND: Finding biomedical named entities is one of the most essential tasks in biomedical text mining. Recently, deep learning-based approaches have been applied to biomedical named entity recognition (BioNER) and showed promising results. Howev...

Supervised methods to extract clinical events from cardiology reports in Italian.

Journal of biomedical informatics
Clinical narratives are a valuable source of information for both patient care and biomedical research. Given the unstructured nature of medical reports, specific automatic techniques are required to extract relevant entities from such texts. In the ...

Diagnosis of Human Psychological Disorders using Supervised Learning and Nature-Inspired Computing Techniques: A Meta-Analysis.

Journal of medical systems
A psychological disorder is a mutilation state of the body that intervenes the imperative functioning of the mind or brain. In the last few years, the number of psychological disorders patients has been significantly raised. This paper presents a com...

Biotechnology, Big Data and Artificial Intelligence.

Biotechnology journal
Developments in biotechnology are increasingly dependent on the extensive use of big data, generated by modern high-throughput instrumentation technologies, and stored in thousands of databases, public and private. Future developments in this area de...

Protecting the Privacy of Cancer Patients Using Fuzzy Association Rule Hiding.

Asian Pacific journal of cancer prevention : APJCP
Objective: Privacy protection in the medical field means the protection of individuals from being associated with undesirable conditions, diagnoses or treatments (Sensitive Attributes). The problem of knowledge discovery from health care data by appl...

Unsupervised feature selection via latent representation learning and manifold regularization.

Neural networks : the official journal of the International Neural Network Society
With the rapid development of multimedia technology, massive unlabelled data with high dimensionality need to be processed. As a means of dimensionality reduction, unsupervised feature selection has been widely recognized as an important and challeng...

Knowledge-guided convolutional networks for chemical-disease relation extraction.

BMC bioinformatics
BACKGROUND: Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highly-structured knowledge bases (KBs), ...

Automating Ischemic Stroke Subtype Classification Using Machine Learning and Natural Language Processing.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: The manual adjudication of disease classification is time-consuming, error-prone, and limits scaling to large datasets. In ischemic stroke (IS), subtype classification is critical for management and outcome prediction. This study sought to...