AIMC Topic: Machine Learning

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Leveraging implicit expert knowledge for non-circular machine learning in sepsis prediction.

Artificial intelligence in medicine
Sepsis is the leading cause of death in non-coronary intensive care units. Moreover, a delay of antibiotic treatment of patients with severe sepsis by only few hours is associated with increased mortality. This insight makes accurate models for early...

Downscaling satellite soil moisture using geomorphometry and machine learning.

PloS one
Annual soil moisture estimates are useful to characterize trends in the climate system, in the capacity of soils to retain water and for predicting land and atmosphere interactions. The main source of soil moisture spatial information across large ar...

Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection.

Neural networks : the official journal of the International Neural Network Society
Since the principal component analysis and its variants are sensitive to outliers that affect their performance and applicability in real world, several variants have been proposed to improve the robustness. However, most of the existing methods are ...

Operation-aware Neural Networks for user response prediction.

Neural networks : the official journal of the International Neural Network Society
User response prediction makes a crucial contribution to the rapid development of online advertising system and recommendation system. The importance of learning feature interactions has been emphasized by many works. Many deep models are proposed to...

Sensitivity Analysis and Extensions of Testing the Causal Direction of Dependence: A Rejoinder to Thoemmes (2019).

Multivariate behavioral research
A commentary by Thoemmes on Wiedermann and Sebastian's introductory article on Direction Dependence Analysis (DDA) is responded to in the interest of elaborating and extending direction dependence principles to evaluate causal effect directionality. ...

Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Patients with 1p/19q codeleted low-grade glioma (LGG) have longer overall survival and better treatment response than patients with 1p/19q intact tumors. Therefore, it is relevant to know the 1p/19q status. To investigate whether the 1p/19q ...

Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method.

Journal of translational medicine
BACKGROUND: Infertility has become a global health issue with the number of couples seeking in vitro fertilization (IVF) worldwide continuing to rise. Some couples remain childless after several IVF cycles. Women undergoing IVF face greater risks and...

Machine learning for discovering missing or wrong protein function annotations : A comparison using updated benchmark datasets.

BMC bioinformatics
BACKGROUND: A massive amount of proteomic data is generated on a daily basis, nonetheless annotating all sequences is costly and often unfeasible. As a countermeasure, machine learning methods have been used to automatically annotate new protein func...

Fusing Object Information and Inertial Data for Activity Recognition.

Sensors (Basel, Switzerland)
In the field of pervasive computing, wearable devices have been widely used for recognizing human activities. One important area in this research is the recognition of activities of daily living where especially inertial sensors and interaction senso...