AIMC Topic: Data Mining

Clear Filters Showing 1451 to 1460 of 1626 articles

Engineering Bias in AI.

IEEE pulse
After working at Apple designing circuits and signal processing algorithms for products including the first iPad, Timnit Gebru (Figure 1) received her Ph.D. from the Stanford Artificial Intelligence Laboratory in the area of computer vision. She rece...

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The increasing amount of scientific literature in biological and biomedical science research has created a challenge in continuous and reliable curation of the latest knowledge discovered, and automatic biomedical text-mining has been one of the answ...

Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning.

Methods in molecular biology (Clifton, N.J.)
The creation of big clinical data cohorts for machine learning and data analysis require a number of steps from the beginning to successful completion. Similar to data set preprocessing in other fields, there is an initial need to complete data quali...

Ontology based text mining of gene-phenotype associations: application to candidate gene prediction.

Database : the journal of biological databases and curation
Gene-phenotype associations play an important role in understanding the disease mechanisms which is a requirement for treatment development. A portion of gene-phenotype associations are observed mainly experimentally and made publicly available throu...

Machine-learning-based patient-specific prediction models for knee osteoarthritis.

Nature reviews. Rheumatology
Osteoarthritis (OA) is an extremely common musculoskeletal disease. However, current guidelines are not well suited for diagnosing patients in the early stages of disease and do not discriminate patients for whom the disease might progress rapidly. T...

Monitoring of Technology Adoption Using Web Content Mining of Location Information and Geographic Information Systems: A Case Study of Digital Breast Tomosynthesis.

JCO clinical cancer informatics
PURPOSE: To our knowledge, integration of Web content mining of publicly available addresses with a geographic information system (GIS) has not been applied to the timely monitoring of medical technology adoption. Here, we explore the diffusion of a ...

Deep learning for healthcare: review, opportunities and challenges.

Briefings in bioinformatics
Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming health care. Various types of data have been emerging in modern biomedical research, including electron...

Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics.

Anesthesia and analgesia
Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical ca...

Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.

Journal of the American Medical Informatics Association : JAMIA
We introduce data assimilation as a computational method that uses machine learning to combine data with human knowledge in the form of mechanistic models in order to forecast future states, to impute missing data from the past by smoothing, and to i...