AIMC Topic: Algorithms

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Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.

IEEE transactions on bio-medical engineering
In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlate...

Feature Selection and Parameters Optimization of Support Vector Machines Based on Hybrid Glowworm Swarm Optimization for Classification of Diabetic Retinopathy.

Journal of medical systems
Diabetic Retinopathy (DR) has been a leading cause of blindness in case of human beings falling between the ages of 20 and 74 years. This will have a major influence on both the patient and the society as it can normally influence the humans in their...

Learning of spatiotemporal patterns in a spiking neural network with resistive switching synapses.

Science advances
The human brain is a complex integrated spatiotemporal system, where space (which neuron fires) and time (when a neuron fires) both carry information to be processed by cognitive functions. To parallel the energy efficiency and computing functionalit...

LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine.

Neural networks : the official journal of the International Neural Network Society
Restricted Boltzmann Machine (RBM) is the building block of Deep Belief Nets and other deep learning tools. Fast learning and prediction are both essential for practical usage of RBM-based machine learning techniques. This paper proposes Lean Contras...

A Novel Method of Segmentation and Classification for Meditation in Health Care Systems.

Journal of medical systems
Meditation improves positivity in behavioral as well as psychological changes, which are brought elucidated by knowing neuro-physiological consequences of meditation. In the field of cognitive science, neuroscience and physiological research, Electro...

Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration.

IEEE journal of biomedical and health informatics
Deformable registration has been one of the pillars of biomedical image computing. Conventional approaches refer to the definition of a similarity criterion that, once endowed with a deformation model and a smoothness constraint, determines the optim...

Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition.

IEEE journal of biomedical and health informatics
Multimodal medical image fusion, emerging as a hot topic, aims to fuse images with complementary multi-source information. In this paper, we propose a novel multimodal medical image fusion method based on structural patch decomposition (SPD) and fuzz...

Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning.

Surgical oncology
Glioblastoma multiforme (GBM) are aggressive brain tumors, which lead to poor overall survival (OS) of patients. OS prediction of GBM patients provides useful information for surgical and treatment planning. Radiomics research attempts at predicting ...

Fuzzy entropy based on differential evolution for breast gland segmentation.

Australasian physical & engineering sciences in medicine
For the diagnosis and treatment of breast tumors, the automatic detection of glands is a crucial step. The true segmentation of the gland is directly related to effective treatment effect of the patient. Therefore, it is necessary to propose an autom...

Identifying health information technology related safety event reports from patient safety event report databases.

Journal of biomedical informatics
OBJECTIVE: The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model featu...