AIMC Topic: Machine Learning

Clear Filters Showing 24381 to 24390 of 34417 articles

Machine-learning prediction of adolescent alcohol use: a cross-study, cross-cultural validation.

Addiction (Abingdon, England)
BACKGROUND AND AIMS: The experience of alcohol use among adolescents is complex, with international differences in age of purchase and individual differences in consumption and consequences. This latter underlines the importance of prediction modelin...

An extensive experimental survey of regression methods.

Neural networks : the official journal of the International Neural Network Society
Regression is a very relevant problem in machine learning, with many different available approaches. The current work presents a comparison of a large collection composed by 77 popular regression models which belong to 19 families: linear and general...

Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks.

BMC bioinformatics
BACKGROUND: Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are requir...

CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research.

BMC bioinformatics
BACKGROUND: Current multi-petaflop supercomputers are powerful systems, but present challenges when faced with problems requiring large machine learning workflows. Complex algorithms running at system scale, often with different patterns that require...

Deep Learning in Image Cytometry: A Review.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and how it is ap...

Research on a learning rate with energy index in deep learning.

Neural networks : the official journal of the International Neural Network Society
The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning rates are tuned over time. In this paper, we propose a novel energy index based optimization...

Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks.

Medical engineering & physics
The main goal of this study is to build an artificial intelligence (AI) architecture for automated extraction of dual-modal image features from both shear-wave elastography (SWE) and B-mode ultrasound, and to evaluate the AI architecture for classifi...

Machine Learning Models for Genetic Risk Assessment of Infants with Non-syndromic Orofacial Cleft.

Genomics, proteomics & bioinformatics
The isolated type of orofacial cleft, termed non-syndromic cleft lip with or without cleft palate (NSCL/P), is the second most common birth defect in China, with Asians having the highest incidence in the world. NSCL/P involves multiple genes and com...

The Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization.

IEEE transactions on pattern analysis and machine intelligence
Fine-grained classification describes the automated recognition of visually similar object categories like birds species. Previous works were usually based on explicit pose normalization, i.e., the detection and description of object parts. However, ...