AIMC Topic: Algorithms

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Protein Crystallization Identification via Fuzzy Model on Linear Neighborhood Representation.

IEEE/ACM transactions on computational biology and bioinformatics
X-ray crystallography is the most popular approach for analyzing protein 3D structure. However, the success rate of protein crystallization is very low (2-10 percent). To reduce the cost of time and resources, lots of computation-based methods are de...

Detection of heavy metal lead in lettuce leaves based on fluorescence hyperspectral technology combined with deep learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The feasibility analysis of fluorescence hyperspectral imaging technology was studied for the detection of lead content in lettuce leaves. Further, Monte Carlo optimized wavelet transform stacked auto-encoders (WT-MC-SAE) was proposed for dimensional...

Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art.

Leukemia & lymphoma
Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technologies in many day-to-day applications. Translation of these advances to the patient's bedside for AI assisted interventions is not yet the norm. With ...

Theory of deep convolutional neural networks III: Approximating radial functions.

Neural networks : the official journal of the International Neural Network Society
We consider a family of deep neural networks consisting of two groups of convolutional layers, a downsampling operator, and a fully connected layer. The network structure depends on two structural parameters which determine the numbers of convolution...

Prediction Models for Agonists and Antagonists of Molecular Initiation Events for Toxicity Pathways Using an Improved Deep-Learning-Based Quantitative Structure-Activity Relationship System.

International journal of molecular sciences
In silico approaches have been studied intensively to assess the toxicological risk of various chemical compounds as alternatives to traditional in vivo animal tests. Among these approaches, quantitative structure-activity relationship (QSAR) analysi...

MedFuseNet: An attention-based multimodal deep learning model for visual question answering in the medical domain.

Scientific reports
Medical images are difficult to comprehend for a person without expertise. The scarcity of medical practitioners across the globe often face the issue of physical and mental fatigue due to the high number of cases, inducing human errors during the di...

DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data.

Nature communications
Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even...

Explaining Predictive Model Performance: An Experimental Study of Data Preparation and Model Choice.

Big data
Although confirmatory modeling has dominated much of applied research in medical, business, and behavioral sciences, modeling large data sets with the goal of accurate prediction has become more widely accepted. The current practice for fitting predi...

The preoperative machine learning algorithm for extremity metastatic disease can predict 90-day and 1-year survival: An external validation study.

Journal of surgical oncology
BACKGROUND: The prediction of survival is valuable to optimize treatment of metastatic long-bone disease. The Skeletal Oncology Research Group (SORG) machine-learning (ML) algorithm has been previously developed and internally validated. The purpose ...

Digital pathology and artificial intelligence in translational medicine and clinical practice.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision ...