AIMC Topic: Algorithms

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Fully automatic cervical vertebrae segmentation framework for X-ray images.

Computer methods and programs in biomedicine
The cervical spine is a highly flexible anatomy and therefore vulnerable to injuries. Unfortunately, a large number of injuries in lateral cervical X-ray images remain undiagnosed due to human errors. Computer-aided injury detection has the potential...

Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Neural networks : the official journal of the International Neural Network Society
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach li...

iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou's pseudo amino acid composition.

Journal of theoretical biology
Membrane proteins execute significant roles in cellular processes of living organisms, ranging from cell signaling to cell adhesion. As a major part of a cell, the identification of membrane proteins and their functional types become a challenging jo...

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

Computer methods and programs in biomedicine
BACKGROUND: Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) co...

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack...

Max-margin weight learning for medical knowledge network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The application of medical knowledge strongly affects the performance of intelligent diagnosis, and method of learning the weights of medical knowledge plays a substantial role in probabilistic graphical models (PGMs). The p...

Construction of mammographic examination process ontology using bottom-up hierarchical task analysis.

Radiological physics and technology
Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and i...

Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.

The British journal of radiology
OBJECTIVE: To train a generic deep learning software (DLS) to classify breast cancer on ultrasound images and to compare its performance to human readers with variable breast imaging experience.

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition.

Journal of chemical information and modeling
Inspired by natural language processing techniques, we here introduce Mol2vec, which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Like the Word2vec models, where vectors of closely related w...

Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways.

Scientific reports
The war on cancer is progressing globally but slowly as researchers around the world continue to seek and discover more innovative and effective ways of curing this catastrophic disease. Organizing biological information, representing it, and making ...