AIMC Topic: Reproducibility of Results

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Nucleus and cytoplasm-based segmentation and actor-critic neural network for acute lymphocytic leukaemia detection in single cell blood smear images.

Medical & biological engineering & computing
Acute lymphoblastic leukaemia (ALL), which is due to the malfunctioning in the bone marrow, is common among people all over the world. The haematologist suffers a lot to discriminate the presence of leukaemia in the patients using the blood smears. T...

Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.

Clinical breast cancer
BACKGROUND: Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to de...

Reconstruction error based deep neural networks for coronary heart disease risk prediction.

PloS one
Coronary heart disease (CHD) is one of the leading causes of death worldwide; if suffering from CHD and being in its end-stage, the most advanced treatments are required, such as heart surgery and heart transplant. Moreover, it is not easy to diagnos...

Deep learning-based virtual noncontrast CT for volumetric modulated arc therapy planning: Comparison with a dual-energy CT-based approach.

Medical physics
PURPOSE: The aim of this study was to develop a deep learning (DL) method for generating virtual noncontrast (VNC) computed tomography (CT) images from contrast-enhanced (CE) CT images (VNC ) and to evaluate its performance in dose calculations for h...

Lower Body Kinematics Monitoring in Running Using Fabric-Based Wearable Sensors and Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Continuous kinematic monitoring of runners is crucial to inform runners of inappropriate running habits. Motion capture systems are the gold standard for gait analysis, but they are spatially limited to laboratories. Recently, wearable sensors have g...

Multimodal deep representation learning for protein interaction identification and protein family classification.

BMC bioinformatics
BACKGROUND: Protein-protein interactions(PPIs) engage in dynamic pathological and biological procedures constantly in our life. Thus, it is crucial to comprehend the PPIs thoroughly such that we are able to illuminate the disease occurrence, achieve ...

An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.

Expert review of gastroenterology & hepatology
: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy in 2018, water exchange colonoscopy and artificial intelligence were both considered important advances. Artificial intelligence holds the potential to...

[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

Nederlands tijdschrift voor geneeskunde
In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since it is an indication for the prescription of oral anticoagulation, instead of anti-platelet therapy, to decrease the chance of a recurrent ischaemic cer...

An interpretation algorithm for molecular diagnosis of bacterial vaginosis in a maternity hospital using machine learning: proof-of-concept study.

Diagnostic microbiology and infectious disease
Allplex Bacterial vaginosis assay (Seegene, South Korea) is a molecular test for bacterial vaginosis (BV). A machine learning algorithm was devised on 200 samples (BV = 23, non-BV = 177) converting 7 identified bacterial strains polymerase chain reac...