AIMC Journal:
Computer methods and programs in biomedicine

Showing 431 to 440 of 844 articles

Explainable artificial intelligence for pharmacovigilance: What features are important when predicting adverse outcomes?

Computer methods and programs in biomedicine Sep 26, 2021
BACKGROUND AND OBJECTIVE: Explainable Artificial Intelligence (XAI) has been identified as a viable method for determining the importance of features when making predictions using Machine Learning (ML) models. In this study, we created models that ta...
Artificial Intelligence Machine Learning Algorithms Aged Humans Australia Pharmacovigilance
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MIDGET:Detecting differential gene expression on microarray data.

Computer methods and programs in biomedicine Sep 16, 2021
Backgound and Objective: Detecting differentially expressed genes is an important step in genome wide analysis and expression profiling. There are a wide array of algorithms used in today's research based on statistical approaches. Even though the cu...
Gene Expression Microarray Analysis Neural Networks, Computer Machine Learning Algorithms
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Dissected aorta segmentation using convolutional neural networks.

Computer methods and programs in biomedicine Sep 15, 2021
BACKGROUND AND OBJECTIVE: Aortic dissection is a severe cardiovascular pathology in which an injury of the intimal layer of the aorta allows blood flowing into the aortic wall, forcing the wall layers apart. Such situation presents a high mortality r...
Computed Tomography Angiography Image Processing, Computer-Assisted Aorta Algorithms Tomography, X-Ray Computed Neural Networks, Computer
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Modality-agnostic self-supervised deep feature learning and fast instance optimisation for multimodal fusion in ultrasound-guided interventions.

Computer methods and programs in biomedicine Sep 13, 2021
BACKGROUND AND OBJECTIVE: Fast and robust alignment of pre-operative MRI planning scans to intra-operative ultrasound is an important aspect for automatically supporting image-guided interventions. Thus far, learning-based approaches have failed to t...
Magnetic Resonance Imaging Ultrasonography, Interventional Motion Neural Networks, Computer Ultrasonography
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Learning the impact of acute and chronic diseases on forecasting neonatal encephalopathy.

Computer methods and programs in biomedicine Sep 13, 2021
OBJECTIVE: There is a wide range of risk factors predisposing to the onset of neonatal encephalopathy (NE), including maternal antepartum/intrapartum comorbidities or events. However, few studies have investigated the difference in the impact of acut...
Risk Factors Chronic Disease Brain Diseases Electronic Health Records Infant, Newborn Humans Machine Learning
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DR-MIL: deep represented multiple instance learning distinguishes COVID-19 from community-acquired pneumonia in CT images.

Computer methods and programs in biomedicine Sep 9, 2021
BACKGROUND AND OBJECTIVE: Given that the novel coronavirus disease 2019 (COVID-19) has become a pandemic, a method to accurately distinguish COVID-19 from community-acquired pneumonia (CAP) is urgently needed. However, the spatial uncertainty and mor...
Humans COVID-19 Deep Learning Pneumonia Tomography, X-Ray Computed SARS-CoV-2
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Applying interpretable deep learning models to identify chronic cough patients using EHR data.

Computer methods and programs in biomedicine Sep 4, 2021
BACKGROUND AND OBJECTIVE: Chronic cough (CC) affects approximately 10% of adults. Many disease states are associated with chronic cough, such as asthma, upper airway cough syndrome, bronchitis, and gastroesophageal reflux disease. The lack of an ICD ...
Prospective Studies Retrospective Studies Deep Learning Electronic Health Records Humans Machine Learning Cough Adult Algorithms
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A multiphase texture-based model of active contours assisted by a convolutional neural network for automatic CT and MRI heart ventricle segmentation.

Computer methods and programs in biomedicine Aug 31, 2021
BACKGROUND: Left and right ventricle automatic segmentation remains one of the more important tasks in computed aided diagnosis. Active contours have shown to be efficient for this task, however they often require user interaction to provide the init...
Radiography Image Processing, Computer-Assisted Heart Ventricles Magnetic Resonance Imaging Neural Networks, Computer Tomography, X-Ray Computed
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A deep learning approach for synthetic MRI based on two routine sequences and training with synthetic data.

Computer methods and programs in biomedicine Aug 31, 2021
BACKGROUND AND OBJECTIVE: Synthetic magnetic resonance imaging (MRI) is a low cost procedure that serves as a bridge between qualitative and quantitative MRI. However, the proposed methods require very specific sequences or private protocols which ha...
Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Brain
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Accurate diagnosis of sepsis using a neural network: Pilot study using routine clinical variables.

Computer methods and programs in biomedicine Aug 31, 2021
BACKGROUND AND OBJECTIVES: Sepsis is a severe infection that increases mortality risk and is one if the main causes of death in intensive care units. Accurate detection is key to successful interventions, but diagnosis of sepsis is complicated becaus...
Humans Sepsis Cross-Sectional Studies Retrospective Studies Neural Networks, Computer Pilot Projects Intensive Care Units Artificial Intelligence
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