AIMC Topic: Humans

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QSAR and deep learning model for virtual screening of potential inhibitors against Inosine 5' Monophosphate dehydrogenase (IMPDH) of Cryptosporidium parvum.

Journal of molecular graphics & modelling
Cryptosporidium parvum (Cp) causes a gastro-intestinal disease called Cryptosporidiosis. C. parvum Inosine 5' monophosphate dehydrogenase (CpIMPDH) is responsible for the production of guanine nucleotides. In the present study, 37 known urea-based co...

Explanation of machine learning models using shapley additive explanation and application for real data in hospital.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: When using machine learning techniques in decision-making processes, the interpretability of the models is important. In the present paper, we adopted the Shapley additive explanation (SHAP), which is based on fair profit al...

Deep learning-based computer-aided heart sound analysis in children with left-to-right shunt congenital heart disease.

International journal of cardiology
OBJECTIVE: The purpose of this study was to explore a new algorithm model capable of leverage deep learning to screen and diagnose specific types of left-to-right shunt congenital heart disease (CHD) in children.

Machine Learning Models Prognosticate Functional Outcomes Better than Clinical Scores in Spontaneous Intracerebral Haemorrhage.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: This study aims to develop and compare the use of deep neural networks (DNN) and support vector machines (SVM) to clinical prognostic scores for prognosticating 30-day mortality and 90-day poor functional outcome (PFO) in spontaneous intra...

Change patterns in the corneal sub-basal nerve and corneal aberrations in patients with dry eye disease: An artificial intelligence analysis.

Experimental eye research
We aimed to investigate the change patterns in corneal sub-basal nerve morphology and corneal intrinsic aberrations in dry eye disease (DED). Our study included 229 eyes of 155 patients with DED and 40 eyes of 20 healthy control. We used the Oculus k...

Deep-learning-assisted algorithm for catheter reconstruction during MR-only gynecological interstitial brachytherapy.

Journal of applied clinical medical physics
Magnetic resonance imaging (MRI) offers excellent soft-tissue contrast enabling the contouring of targets and organs at risk during gynecological interstitial brachytherapy procedure. Despite its advantage, one of the main obstacles preventing a tran...

Deep graph convolutional network for US birth data harmonization.

Journal of biomedical informatics
In this paper, we developed a feasible and efficient deep-learning-based framework to combine the United States (US) natality data for the last five decades, with changing variables and factors, into a consistent database. We constructed a graph base...

A deep learning method for eliminating head motion artifacts in computed tomography.

Medical physics
PURPOSE: Involuntary patient movement results in data discontinuities during computed tomography (CT) scans which lead to a serious degradation in the image quality. In this paper, we specifically address artifacts induced by patient motion during a ...

Predicting Human Motion Signals Using Modern Deep Learning Techniques and Smartphone Sensors.

Sensors (Basel, Switzerland)
The global adoption of smartphone technology affords many conveniences, and not surprisingly, healthcare applications using wearable sensors like smartphones have received much attention. Among the various potential applications and research related ...