AIMC Topic: Machine Learning

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An Intelligent Fusion Model with Portfolio Selection and Machine Learning for Stock Market Prediction.

Computational intelligence and neuroscience
Developing reliable equity market models allows investors to make more informed decisions. A trading model can reduce the risks associated with investment and allow traders to choose the best-paying stocks. However, stock market analysis is complicat...

Memory augmented recurrent neural networks for de-novo drug design.

PloS one
A recurrent neural network (RNN) is a machine learning model that learns the relationship between elements of an input series, in addition to inferring a relationship between the data input to the model and target output. Memory augmentation allows t...

Exploring Characteristics of Homicide Offenders With Schizophrenia Spectrum Disorders Via Machine Learning.

International journal of offender therapy and comparative criminology
The link between schizophrenia and homicide has long been the subject of research with significant impact on mental health policy, clinical practice, and public perception of people with psychiatric disorders. The present study investigates factors c...

An Online Prognostic Application for Melanoma Based on Machine Learning and Statistics.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Melanoma is a common cancer that causes a severe socioeconomic burden. Patients usually turn to plastic surgeons to determine their prognosis after surgery.

Exploring Built-Up Indices and Machine Learning Regressions for Multi-Temporal Building Density Monitoring Based on Landsat Series.

Sensors (Basel, Switzerland)
Uncontrolled built-up area expansion and building densification could bring some detrimental problems in social and economic aspects such as social inequality, urban heat islands, and disturbance in urban environments. This study monitored multi-deca...

Machine learning methods to predict attrition in a population-based cohort of very preterm infants.

Scientific reports
The timely identification of cohort participants at higher risk for attrition is important to earlier interventions and efficient use of research resources. Machine learning may have advantages over the conventional approaches to improve discriminati...

Stroke Risk Prediction with Machine Learning Techniques.

Sensors (Basel, Switzerland)
A stroke is caused when blood flow to a part of the brain is stopped abruptly. Without the blood supply, the brain cells gradually die, and disability occurs depending on the area of the brain affected. Early recognition of symptoms can significantly...

Machine Learning Techniques Based on Primary User Emulation Detection in Mobile Cognitive Radio Networks.

Sensors (Basel, Switzerland)
Mobile cognitive radio networks (MCRNs) have arisen as an alternative mobile communication because of the spectrum scarcity in actual mobile technologies such as 4G and 5G networks. MCRN uses the spectral holes of a primary user (PU) to transmit its ...

Automation of Cephalometrics Using Machine Learning Methods.

Computational intelligence and neuroscience
Cephalometry is a medical test that can detect teeth, skeleton, or appearance problems. In this scenario, the patient's lateral radiograph of the face was utilised to construct a tracing from the tracing of lines on the lateral radiograph of the face...