AIMC Topic: Research Design

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Classifying chest CT images as COVID-19 positive/negative using a convolutional neural network ensemble model and uniform experimental design method.

BMC bioinformatics
BACKGROUND: To classify chest computed tomography (CT) images as positive or negative for coronavirus disease 2019 (COVID-19) quickly and accurately, researchers attempted to develop effective models by using medical images.

Environmental sound classification using temporal-frequency attention based convolutional neural network.

Scientific reports
Environmental sound classification is one of the important issues in the audio recognition field. Compared with structured sounds such as speech and music, the time-frequency structure of environmental sounds is more complicated. In order to learn ti...

Heterogeneous treatment effect analysis based on machine-learning methodology.

CPT: pharmacometrics & systems pharmacology
Heterogeneous treatment effect (HTE) analysis focuses on examining varying treatment effects for individuals or subgroups in a population. For example, an HTE-informed understanding can critically guide physicians to individualize the medical treatme...

Breast Mass Classification Using Diverse Contextual Information and Convolutional Neural Network.

Biosensors
Masses are one of the early signs of breast cancer, and the survival rate of women suffering from breast cancer can be improved if masses can be correctly identified as benign or malignant. However, their classification is challenging due to the simi...

Chip Appearance Defect Recognition Based on Convolutional Neural Network.

Sensors (Basel, Switzerland)
To improve the recognition rate of chip appearance defects, an algorithm based on a convolution neural network is proposed to identify chip appearance defects of various shapes and features. Furthermore, to address the problems of long training time ...

Artificial Intelligence Applications in Urology: Reporting Standards to Achieve Fluency for Urologists.

The Urologic clinics of North America
The growth and adoption of artificial intelligence has led to impressive results in urology. As artificial intelligence grows more ubiquitous, it is important to establish artificial intelligence literacy in the workforce. To this end, we present a n...

RTJTN: Relational Triplet Joint Tagging Network for Joint Entity and Relation Extraction.

Computational intelligence and neuroscience
Extracting entities and relations from unstructured sentences is one of the most concerned tasks in the field of natural language processing. However, most existing works process entity and relation information in a certain order and suffer from the ...

The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

BMC cardiovascular disorders
BACKGROUND: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar electrocardiographic (ECG) patterns, characterized by ST-segment elevation in the right precordial leads, and risk of Sudden Cardiac Death (SCD). Furthe...

Intelligent Solutions in Chest Abnormality Detection Based on YOLOv5 and ResNet50.

Journal of healthcare engineering
Computer-aided diagnosis (CAD) has nearly fifty years of history and has assisted many clinicians in the diagnosis. With the development of technology, recently, researches use the deep learning method to get high accuracy results in the CAD system. ...

COVID-19 Diagnosis from CT Images with Convolutional Neural Network Optimized by Marine Predator Optimization Algorithm.

BioMed research international
In recent years, almost every country in the world has struggled against the spread of Coronavirus Disease 2019. If governments and public health systems do not take action against the spread of the disease, it will have a severe impact on human life...