STDs

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 black-box testing. Compared with other automated testing approaches, automatic robotic testing can reduce the dependence on the internal information of apps. However, capturing GUI element information accurately and effectively from a black-box perspective is a critical issue in robotic testing. This...

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 identical conditions), but also 'reproducible' (replicable in other laboratories under similar conditions). Results should also, if possible, be 'robust' (replicable under a wide range of conditions). The reproducibility and robustness of only a small fraction of published biomedical results has been tested...

Deep learning-based anomaly detection from ultrasonic images.

Non-destructive testing is a group of methods for evaluating the integrity of components. Among them, ultrasonic inspection stands out due to its abil...

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 of a fluid to render predictable changes in mechan...

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) interventions (PARRI), have played a subsidiary role in ...

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 interest among a large set of biomarker measurements...

INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network.

Testing is one of the important methodologies used by various countries in order to fight against COVID-19 infection. The infection is considered as o...

Interpretable tumor differentiation grade and microsatellite instability recognition in gastric cancer using deep learning.

Gastric cancer possesses great histological and molecular diversity, which creates obstacles for rapid and efficient diagnoses. Classic diagnoses eith...

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized...

CVDF DYNAMIC-A Dynamic Fuzzy Testing Sample Generation Framework Based on BI-LSTM and Genetic Algorithm.

As one of the most effective methods of vulnerability mining, fuzzy testing has scalability and complex path detection ability. Fuzzy testing sample g...

Deep Modular Bilinear Attention Network for Visual Question Answering.

VQA (Visual Question Answering) is a multi-model task. Given a picture and a question related to the image, it will determine the correct answer. The ...

Advanced Deep Learning Human Herpes Virus 6 (HHV-6) Molecular Detection in Understanding Human Infertility.

To see if HHV-6 may be a cause of infertility, researchers looked at 18 men and 10 women who had unexplained critical fertility and had at least one p...

Deep learning based cervical screening by the cross-modal integration of colposcopy, cytology, and HPV test.

PURPOSE: To develop and evaluate the colposcopy based deep learning model using all kinds of cervical images for cervical screening, and investigate t...

Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy.

This study is aimed at evaluating a deep transfer learning-based model for identifying diabetic retinopathy (DR) that was trained using a dataset with...

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless,...

Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon.

INTRODUCTION: Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issu...

The development of "automated visual evaluation" for cervical cancer screening: The promise and challenges in adapting deep-learning for clinical testing: Interdisciplinary principles of automated visual evaluation in cervical screening.

There is limited access to effective cervical cancer screening programs in many resource-limited settings, resulting in continued high cervical cancer...

Drug repurposing for COVID-19 using graph neural network and harmonizing multiple evidence.

Since the 2019 novel coronavirus disease (COVID-19) outbreak in 2019 and the pandemic continues for more than one year, a vast amount of drug research...

A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR's) Operating Environment-A Case Study.

The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technol...

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images.

Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to det...