AIMC Topic: Big Data

Clear Filters Showing 401 to 410 of 659 articles

Salience-aware adaptive resonance theory for large-scale sparse data clustering.

Neural networks : the official journal of the International Neural Network Society
Sparse data is known to pose challenges to cluster analysis, as the similarity between data tends to be ill-posed in the high-dimensional Hilbert space. Solutions in the literature typically extend either k-means or spectral clustering with additiona...

[E-health and "Cancer outside the hospital walls", Big Data and artificial intelligence].

Bulletin du cancer
To heal otherwise in oncology has become an imperative of Public Health and an economic imperative in France. Patients can therefore receive live most of their care outside of hospital with more ambulatory care. This ambulatory shift will benefit fro...

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.

Bipolar disorders
OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learnin...

Big Data and Artificial Intelligence Modeling for Drug Discovery.

Annual review of pharmacology and toxicology
Due to the massive data sets available for drug candidates, modern drug discovery has advanced to the big data era. Central to this shift is the development of artificial intelligence approaches to implementing innovative modeling based on the dynami...

Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learning.

Scientific reports
Artificial intelligence (AI) is expected to support clinical judgement in medicine. We constructed a new predictive model for diabetic kidney diseases (DKD) using AI, processing natural language and longitudinal data with big data machine learning, b...

A deep learning model for real-time mortality prediction in critically ill children.

Critical care (London, England)
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...