Journal of molecular graphics & modelling
Jul 24, 2019
Learning-to-rank, which is a machine-learning technique for information retrieval, was recently introduced to ligand-based virtual screening to reduce the costs of developing a new drug. The quality of a rank prediction model depends on experimental ...
BACKGROUND: The variation in articular cartilage thickness (ACT) in healthy knees is difficult to quantify and therefore poorly documented. Our aims are to (1) define how machine learning (ML) algorithms can automate the segmentation and measurement ...
Computer methods and programs in biomedicine
Jul 24, 2019
BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD) is one of the commonest diseases around the world. An early and accurate diagnosis of CAD allows a timely administration of appropriate treatment and helps to reduce the mortality. Herein, we de...
BACKGROUND: Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PG...
BACKGROUND: Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. The cost and infrastructure challenges required to implement this is prohibitive for most hospitals. Natural lang...
In medical image processing, Brain tumor segmentation plays an important role. Early detection of these tumors is highly required to give Treatment of patients. The patient's life chances are improved by the early detection of it. The process of diag...
Computational intelligence and neuroscience
Jul 24, 2019
This paper explores the model parameters estimation of a quadrotor UAV by exploiting the cooperative particle swarm optimization-cuckoo search (PSO-CS). The PSO-CS regulates the convergence velocity benefiting from the capabilities of social thinking...
There is extensive evidence that biological neural networks encode information in the precise timing of the spikes generated and transmitted by neurons, which offers several advantages over rate-based codes. Here we adopt a vector space formulation o...
Existing brain region segmentation algorithms based on deep convolutional neural networks (CNN) are inefficient for object boundary segmentation. In order to enhance the segmentation accuracy of brain tissue, this paper proposed an object region segm...
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