AI Medical Compendium Topic:
Data Mining

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Machine learning technology in the application of genome analysis: A systematic review.

Gene
Machine learning (ML) is a powerful technique to tackle many problems in data mining and predictive analytics. We believe that ML will be of considerable potentials in the field of bioinformatics since the high-throughput technology is producing ever...

PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison.

BMC bioinformatics
BACKGROUND: Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene variant - drug - adverse ev...

Machine learning and complex biological data.

Genome biology
Machine learning has demonstrated potential in analyzing large, complex biological data. In practice, however, biological information is required in addition to machine learning for successful application.

Identifying Factors That Affect Patient Survival After Orthotopic Liver Transplant Using Machine-Learning Techniques.

Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation
OBJECTIVES: Survival after liver transplant depends on pretransplant, peritransplant, and posttransplant factors. Identifying effective factors for patient survival after transplant can help transplant centers make better decisions.

Mining Implicit Treatment Concepts for Neural Precision Medicine.

IEEE transactions on nanobioscience
Precision medicine (PM) is regarded as an information retrieval (IR) task in which biomedical articles containing treatment information about specific diseases or genetic variants are retrieved in response to patient record for the purpose of providi...

Hierarchical sequence labeling for extracting BEL statements from biomedical literature.

BMC medical informatics and decision making
BACKGROUND: Extracting relations between bio-entities from biomedical literature is often a challenging task and also an essential step towards biomedical knowledge expansion. The BioCreative community has organized a shared task to evaluate the robu...

On building a diabetes centric knowledge base via mining the web.

BMC medical informatics and decision making
BACKGROUND: Diabetes has become one of the hot topics in life science researches. To support the analytical procedures, researchers and analysts expend a mass of labor cost to collect experimental data, which is also error-prone. To reduce the cost a...

Large-scale quantitative profiling of the Old English verse tradition.

Nature human behaviour
The corpus of Old English verse is an indispensable source for scholars of the Indo-European tradition, early Germanic culture and English literary history. Although it has been the focus of sustained literary scholarship for over two centuries, Old ...

Document-level attention-based BiLSTM-CRF incorporating disease dictionary for disease named entity recognition.

Computers in biology and medicine
BACKGROUND: Disease named entity recognition (NER) plays an important role in biomedical research. There are a significant number of challenging issues to be addressed; among these, the identification of rare diseases and complex disease names and th...

Applications of Machine Learning in Real-Life Digital Health Interventions: Review of the Literature.

Journal of medical Internet research
BACKGROUND: Machine learning has attracted considerable research interest toward developing smart digital health interventions. These interventions have the potential to revolutionize health care and lead to substantial outcomes for patients and medi...