STDs

Neural Network Detection of Pacemakers for MRI Safety.

Flagging the presence of cardiac devices such as pacemakers before an MRI scan is essential to allow...

The signature-testing approach to mapping biological and artificial intelligences.

Making inferences from behaviour to cognition is problematic due to a many-to-one mapping problem, i...

Decoupling RNN Training and Testing Observation Intervals for Spectrum Sensing Applications.

Recurrent neural networks have been shown to outperform other architectures when processing temporal...

Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice: A Methodologic Framework for Clinical Testing of Artificial Intelligence Tools.

Robot and mechanical testing of a specialist manual toothbrush for cleaning efficacy and improved force control.

BACKGROUND: Toothbrushes require flexibility to access all dental surfaces and remove plaque effecti...

Predicting early failure of quantum cascade lasers during accelerated burn-in testing using machine learning.

Device life time is a significant consideration in the cost of ownership of quantum cascade lasers (...

Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell-based drug cardiotoxicity testing.

Utilizing recent advances in human induced pluripotent stem cell (hiPSC) technology, nonlinear analy...

Patient Benefit and Quality of Life after Robot-Assisted Head and Neck Surgery.

Robotic systems for head and neck surgery are at different stages of technical development and clini...

A deep learning based method for intelligent detection of seafarers' mental health condition.

Mental health monitoring of seafarers is an important part of achieving normal development of the oc...

Replacement of animal testing by integrated approaches to testing and assessment (IATA): a call for in vivitrosi.

Alternative methods to animal use in toxicology are evolving with new advanced tools and multilevel ...

Memory Recall: A Simple Neural Network Training Framework Against Catastrophic Forgetting.

It is widely acknowledged that biological intelligence is capable of learning continually without fo...

Visual Identification of Mobile App GUI Elements for Automated Robotic Testing.

Automated robotic testing is an emerging testing approach for mobile apps that can afford complete b...

Antilogic, a new supervised machine learning software for the automatic interpretation of antibiotic susceptibility testing in clinical microbiology: proof-of-concept on three frequently isolated bacterial species.

OBJECTIVE: Antibiotic susceptibility testing (AST) is necessary in order to adjust empirical antibio...

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and i...

Testing the reproducibility and robustness of the cancer biology literature by robot.

Scientific results should not just be 'repeatable' (replicable in the same laboratory under identica...

Deep learning-based anomaly detection from ultrasonic images.

Non-destructive testing is a group of methods for evaluating the integrity of components. Among them...

3D-Printed Soft Sensors for Adaptive Sensing with Online and Offline Tunable Stiffness.

The stiffness of a soft robot with structural cavities can be regulated by controlling the pressure ...

Reflex and reflective laboratory interventions for adding value to test results; an integral part of laboratory stewardship.

Post-analytical reflexive (automated) and/or reflective (patient tailored and thought driven) interv...

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features.

BACKGROUND AND OBJECTIVE: Radiomics and deep learning have emerged as two distinct approaches to med...

CPG-based generation strategy of variable rhythmic chewing movements for a dental testing chewing robot.

The rhythmic chewing movement pattern is dynamically reshaped to adapt to a variable chewing environ...

Testing a global null hypothesis using ensemble machine learning methods.

Testing a global null hypothesis that there are no significant predictors for a binary outcome of in...