AI Medical Compendium Topic:
Unsupervised Machine Learning

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Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease.

International journal of neural systems
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the constr...

Classifying Force Spectroscopy of DNA Pulling Measurements Using Supervised and Unsupervised Machine Learning Methods.

Journal of chemical information and modeling
Dynamic force spectroscopy (DFS) measurements on biomolecules typically require classifying thousands of repeated force spectra prior to data analysis. Here, we study classification of atomic force microscope-based DFS measurements using machine-lear...

A Feature Learning and Object Recognition Framework for Underwater Fish Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Live fish recognition is one of the most crucial elements of fisheries survey applications where the vast amount of data is rapidly acquired. Different from general scenarios, challenges to underwater image recognition are posted by poor image qualit...

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.

IEEE transactions on medical imaging
Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlab...

Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

Medical engineering & physics
We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the sui...

An unsupervised learning method to identify reference intervals from a clinical database.

Journal of biomedical informatics
Reference intervals are critical for the interpretation of laboratory results. The development of reference intervals using traditional methods is time consuming and costly. An alternative approach, known as an a posteriori method, requires an expert...

Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

IEEE transactions on bio-medical engineering
Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection,...

Unsupervised Trajectory Segmentation for Surgical Gesture Recognition in Robotic Training.

IEEE transactions on bio-medical engineering
Dexterity and procedural knowledge are two critical skills that surgeons need to master to perform accurate and safe surgical interventions. However, current training systems do not allow us to provide an in-depth analysis of surgical gestures to pre...

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems.

Scientific reports
Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitiv...