AIMC Topic: Machine Learning

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Protein interaction network constructing based on text mining and reinforcement learning with application to prostate cancer.

IET systems biology
Constructing interaction network from biomedical texts is a very important and interesting work. The authors take advantage of text mining and reinforcement learning approaches to establish protein interaction network. Considering the high computatio...

Emergency Department Visit Forecasting and Dynamic Nursing Staff Allocation Using Machine Learning Techniques With Readily Available Open-Source Software.

Computers, informatics, nursing : CIN
Although emergency department visit forecasting can be of use for nurse staff planning, previous research has focused on models that lacked sufficient resolution and realistic error metrics for these predictions to be applied in practice. Using data ...

[Algorithms, machine intelligence, big data : general considerations].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
We are experiencing astonishing developments in the areas of big data and artificial intelligence. They follow a pattern that we have now been observing for decades: according to Moore's Law,the performance and efficiency in the area of elementary ar...

Classifying pairs with trees for supervised biological network inference.

Molecular bioSystems
Networks are ubiquitous in biology, and computational approaches have been largely investigated for their inference. In particular, supervised machine learning methods can be used to complete a partially known network by integrating various measureme...

[Dynamic Detection of Fresh Jujube Based on ELM and Visible/Near Infrared Spectra].

Guang pu xue yu guang pu fen xi = Guang pu
Jujube was rich in nutrition and variety. In different varieties, there were very different from the market price to the qualities of internal and external. In order to realize the rapid and non-destructive detection of fresh jujubes' classification,...

Evolutionary game dynamics of controlled and automatic decision-making.

Chaos (Woodbury, N.Y.)
We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or contro...

Use of Machine Learning to Identify Children with Autism and Their Motor Abnormalities.

Journal of autism and developmental disorders
In the present work, we have undertaken a proof-of-concept study to determine whether a simple upper-limb movement could be useful to accurately classify low-functioning children with autism spectrum disorder (ASD) aged 2-4. To answer this question, ...

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space.

The journal of physical chemistry letters
Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and ap...

Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery.

Bioinformatics (Oxford, England)
MOTIVATION: Despite ongoing cancer research, available therapies are still limited in quantity and effectiveness, and making treatment decisions for individual patients remains a hard problem. Established subtypes, which help guide these decisions, a...

Validating FMEA output against incident learning data: A study in stereotactic body radiation therapy.

Medical physics
PURPOSE: Though failure mode and effects analysis (FMEA) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge, its output has never been validated against data on errors that actually occur. The objective of this...