AIMC Topic: Humans

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Time-resolved evaluation of compound repositioning predictions on a text-mined knowledge network.

BMC bioinformatics
BACKGROUND: Computational compound repositioning has the potential for identifying new uses for existing drugs, and new algorithms and data source aggregation strategies provide ever-improving results via in silico metrics. However, even with these a...

Machine-learning based patient classification using Hepatitis B virus full-length genome quasispecies from Asian and European cohorts.

Scientific reports
Chronic infection with Hepatitis B virus (HBV) is a major risk factor for the development of advanced liver disease including fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The relative contribution of virological factors to disease progres...

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.

PloS one
Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted preven...

A novel one-class classification approach to accurately predict disease-gene association in acute myeloid leukemia cancer.

PloS one
Disease causing gene identification is considered as an important step towards drug design and drug discovery. In disease gene identification and classification, the main aim is to identify disease genes while identifying non-disease genes are of les...

Exploring the perceptions of people with dementia about the social robot PARO in a hospital setting.

Dementia (London, England)
New technology, such as social robots, opens up new opportunities in hospital settings. PARO, a robotic pet seal, was designed to provide emotional and social support for older people with dementia. We applied video-ethnographic methods, including co...

Medication-rights detection using incident reports: A natural language processing and deep neural network approach.

Health informatics journal
Medication errors often occurred due to the breach of medication rights that are the right patient, the right drug, the right time, the right dose and the right route. The aim of this study was to develop a medication-rights detection system using na...

Predictors for trifecta achievement of robot-assisted partial nephrectomy in high-complexity tumors (Preoperative Aspects and Dimensions Used for an Anatomical score ≥10).

Asian journal of endoscopic surgery
INTRODUCTION: Robot-assisted partial nephrectomy (RAPN) is emerging as an effective treatment oncologically and functionally for clinically localized renal tumors. However, RAPN in high-complexity tumors with a Preoperative Aspects and Dimensions Use...

Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction.

Journal of neurointerventional surgery
BACKGROUND: Angiographic parametric imaging (API), based on digital subtraction angiography (DSA), is a quantitative imaging tool that may be used to extract contrast flow parameters related to hemodynamic conditions in abnormal pathologies such as i...

EMS-Net: A Deep Learning Method for Autodetecting Epileptic Magnetoencephalography Spikes.

IEEE transactions on medical imaging
Epilepsy is a neurological disorder characterized by sudden and unpredictable epileptic seizures, which incurs significant negative impacts on patients' physical, psychological and social health. A practical approach to assist with the clinical asses...

A novel machine learning based computational framework for homogenization of heterogeneous soft materials: application to liver tissue.

Biomechanics and modeling in mechanobiology
Real-time simulation of organs increases comfort and safety for patients during the surgery. Proper generalized decomposition (PGD) is an efficient numerical method with coordinate errors below 1 mm and response time below 0.1 s that can be used for ...