AIMC Topic: Machine Learning

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Machine learning based identification of relevant parameters for functional voice disorders derived from endoscopic high-speed recordings.

Scientific reports
In voice research and clinical assessment, many objective parameters are in use. However, there is no commonly used set of parameters that reflect certain voice disorders, such as functional dysphonia (FD); i.e. disorders with no visible anatomical c...

Don't dismiss logistic regression: the case for sensible extraction of interactions in the era of machine learning.

BMC medical research methodology
BACKGROUND: Machine learning approaches have become increasingly popular modeling techniques, relying on data-driven heuristics to arrive at its solutions. Recent comparisons between these algorithms and traditional statistical modeling techniques ha...

Machine learning-based prediction of transfusion.

Transfusion
BACKGROUND: The ability to predict transfusions arising during hospital admission might enable economized blood supply management and might furthermore increase patient safety by ensuring a sufficient stock of red blood cells (RBCs) for a specific pa...

A technical review of canonical correlation analysis for neuroscience applications.

Human brain mapping
Collecting comprehensive data sets of the same subject has become a standard in neuroscience research and uncovering multivariate relationships among collected data sets have gained significant attentions in recent years. Canonical correlation analys...

Role of artificial intelligence and vibrational spectroscopy in cancer diagnostics.

Expert review of molecular diagnostics
INTRODUCTION: Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These tech...

Learning personalized ADL recognition models from few raw data.

Artificial intelligence in medicine
Recognition of activities of daily living (ADL) is an essential component of assisted living systems based on actigraphy. This task can nowadays be performed by machine learning models which are able to automatically extract and learn relevant featur...

Feature Selection for High-Dimensional and Imbalanced Biomedical Data Based on Robust Correlation Based Redundancy and Binary Grasshopper Optimization Algorithm.

Genes
The training machine learning algorithm from an imbalanced data set is an inherently challenging task. It becomes more demanding with limited samples but with a massive number of features (high dimensionality). The high dimensional and imbalanced dat...

Brain-Computer Interface-Based Humanoid Control: A Review.

Sensors (Basel, Switzerland)
A Brain-Computer Interface (BCI) acts as a communication mechanism using brain signals to control external devices. The generation of such signals is sometimes independent of the nervous system, such as in Passive BCI. This is majorly beneficial for ...

Explaining the Rationale of Deep Learning Glaucoma Decisions with Adversarial Examples.

Ophthalmology
PURPOSE: To illustrate what is inside the so-called black box of deep learning models (DLMs) so that clinicians can have greater confidence in the conclusions of artificial intelligence by evaluating adversarial explanation on its ability to explain ...