AIMC Topic: Software

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A microsurgical robot research platform for robot-assisted microsurgery research and training.

International journal of computer assisted radiology and surgery
PURPOSE: Ocular surgery, ear, nose and throat surgery and neurosurgery are typical types of microsurgery. A versatile training platform can assist microsurgical skills development and accelerate the uptake of robot-assisted microsurgery (RAMS). Howev...

Research on OpenCL optimization for FPGA deep learning application.

PloS one
In recent years, with the development of computer science, deep learning is held as competent enough to solve the problem of inference and learning in high dimensional space. Therefore, it has received unprecedented attention from both the academia a...

LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets.

Journal of chemical information and modeling
Machine learning algorithms have attained widespread use in assessing the potential toxicities of pharmaceuticals and industrial chemicals because of their faster speed and lower cost compared to experimental bioassays. Gradient boosting is an effect...

AIKYATAN: mapping distal regulatory elements using convolutional learning on GPU.

BMC bioinformatics
BACKGROUND: The data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specific functional annotation problem, within the b...

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice.

G3 (Bethesda, Md.)
Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine ma...

Cell fishing: A similarity based approach and machine learning strategy for multiple cell lines-compound sensitivity prediction.

PloS one
The prediction of cell-lines sensitivity to a given set of compounds is a very important factor in the optimization of in-vitro assays. To date, the most common prediction strategies are based upon machine learning or other quantitative structure-act...

A machine learning-based service for estimating quality of genomes using PATRIC.

BMC bioinformatics
BACKGROUND: Recent advances in high-volume sequencing technology and mining of genomes from metagenomic samples call for rapid and reliable genome quality evaluation. The current release of the PATRIC database contains over 220,000 genomes, and curre...

CNN-based diagnosis models for canine ulcerative keratitis.

Scientific reports
The purpose of this methodological study was to develop a convolutional neural network (CNN), which is a recently developed deep-learning-based image recognition method, to determine corneal ulcer severity in dogs. The CNN model was trained with imag...

DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning.

eLife
Quantitative behavioral measurements are important for answering questions across scientific disciplines-from neuroscience to ecology. State-of-the-art deep-learning methods offer major advances in data quality and detail by allowing researchers to a...

Recognizing software names in biomedical literature using machine learning.

Health informatics journal
Software tools now are essential to research and applications in the biomedical domain. However, existing software repositories are mainly built using manual curation, which is time-consuming and unscalable. This study took the initiative to manually...