AIMC Topic: Machine Learning

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: High-Throughput Quantification of Fluorescent Synaptic Protein Puncta by Machine Learning.

eNeuro
Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual anal...

Protein structure modeling and refinement by global optimization in CASP12.

Proteins
For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequ...

Prediction of persistent hemodynamic depression after carotid angioplasty and stenting using artificial neural network model.

Clinical neurology and neurosurgery
OBJECTIVES: To assess and compare predictive factors for persistent hemodynamic depression (PHD) after carotid artery angioplasty and stenting (CAS) using artificial neural network (ANN) and multiple logistic regression (MLR) or support vector machin...

Towards deep learning with segregated dendrites.

eLife
Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning alg...

DNA Cryptography and Deep Learning using Genetic Algorithm with NW algorithm for Key Generation.

Journal of medical systems
Cryptography is not only a science of applying complex mathematics and logic to design strong methods to hide data called as encryption, but also to retrieve the original data back, called decryption. The purpose of cryptography is to transmit a mess...

Obstacle Detection as a Safety Alert in Augmented Reality Models by the Use of Deep Learning Techniques.

Sensors (Basel, Switzerland)
Augmented reality (AR) is becoming increasingly popular due to its numerous applications. This is especially evident in games, medicine, education, and other areas that support our everyday activities. Moreover, this kind of computer system not only ...

Biopsy-Free Prediction of Pathologic Type of Primary Nephrotic Syndrome Using a Machine Learning Algorithm.

Kidney & blood pressure research
BACKGROUND/AIMS: Renal biopsy is the gold standard to determine the pathologic type of primary nephrotic syndrome, which is critical for diagnosis, choice of treatment and evaluation of prognosis. However, in some cases, renal biopsy cannot be perfor...

A Novel Method of Synovitis Stratification in Ultrasound Using Machine Learning Algorithms: Results From Clinical Validation of the MEDUSA Project.

Ultrasound in medicine & biology
Ultrasound is widely used in the diagnosis and follow-up of chronic arthritis. We present an evaluation of a novel automatic ultrasound diagnostic tool based on image recognition technology. Methods used in developing the algorithm are described else...

An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study.

The Journal of forensic odonto-stomatology
BACKGROUND: Automated methods to evaluate growth of hand and wrist bones on radiographs and magnetic resonance imaging have been developed. They can be applied to estimate age in children and subadults. Automated methods require the software to (1) r...

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

BMC bioinformatics
BACKGROUND: Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human sp...