AIMC Topic: Machine Learning

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How (Not) to Generate a Highly Predictive Biomarker Panel Using Machine Learning.

Journal of proteome research
This review "teaches" researchers how to make their lackluster proteomics data look really impressive, by applying an inappropriate but pervasive strategy that selects features in a biased manner. The strategy is demonstrated and used to build a clas...

A Machine Learning Approach to Improve Ranging Accuracy with AoA and RSSI.

Sensors (Basel, Switzerland)
Ranging accuracy is a critical parameter in time-based indoor positioning systems. Indoor environments often have complex structures, which make centimeter-level-accurate ranging a challenging task. This study proposes a new distance measurement meth...

ResSUMO: A Deep Learning Architecture Based on Residual Structure for Prediction of Lysine SUMOylation Sites.

Cells
Lysine SUMOylation plays an essential role in various biological functions. Several approaches integrating various algorithms have been developed for predicting SUMOylation sites based on a limited dataset. Recently, the number of identified SUMOylat...

Predicting genes associated with RNA methylation pathways using machine learning.

Communications biology
RNA methylation plays an important role in functional regulation of RNAs, and has thus attracted an increasing interest in biology and drug discovery. Here, we collected and collated transcriptomic, proteomic, structural and physical interaction data...

Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is rapidly expanding in medicine despite a lack of consensus on its application and evaluation.

Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings.

Computational intelligence and neuroscience
In the past, large earthquakes caused the collapse of infrastructure and killed thousands of people in Pakistan, a seismically active region. Therefore, the seismic assessment of infrastructure is a dire need that can be done using the fragility anal...

An Assessment of Lexical, Network, and Content-Based Features for Detecting Malicious URLs Using Machine Learning and Deep Learning Models.

Computational intelligence and neuroscience
The World Wide Web services are essential in our daily lives and are available to communities through Uniform Resource Locator (URL). Attackers utilize such means of communication and create malicious URLs to conduct fraudulent activities and deceive...

Tumor Microenvironment, Radiology, and Artificial Intelligence: Should We Consider Tumor Periphery?

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: The tumor microenvironment (TME) consists of cellular and noncellular components which enable the tumor to interact with its surroundings and plays an important role in the tumor progression and how the immune system reacts to the maligna...

Comparisons of deep learning and machine learning while using text mining methods to identify suicide attempts of patients with mood disorders.

Journal of affective disorders
BACKGROUND: Suicide attempt is one of the most severe consequences for patients with mood disorders. This study aimed to perform deep learning and machine learning while using text mining to identify patients with suicide attempts and to compare thei...

A framework for falsifiable explanations of machine learning models with an application in computational pathology.

Medical image analysis
In recent years, deep learning has been the key driver of breakthrough developments in computational pathology and other image based approaches that support medical diagnosis and treatment. The underlying neural networks as inherent black boxes lack ...