AIMC Topic: Humans

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Dark corner artefact and diagnostic performance of a market-approved neural network for skin cancer classification.

Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG
BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNN) have proven dermatologist-level performance in skin lesion classification. Prior to a broader clinical application, an assessment of limitations is crucial. Therefore, the influence of a ...

Testing the Use of Natural Language Processing Software and Content Analysis to Analyze Nursing Hand-off Text Data.

Computers, informatics, nursing : CIN
Natural language processing software programs are used primarily to mine both structured and unstructured data from the electronic health record and other healthcare databases. The mined data are used, for example, to identify vulnerable at-risk popu...

Toward an Automatic Quality Assessment of Voice-Based Telemedicine Consultations: A Deep Learning Approach.

Sensors (Basel, Switzerland)
Maintaining a high quality of conversation between doctors and patients is essential in telehealth services, where efficient and competent communication is important to promote patient health. Assessing the quality of medical conversations is often h...

Integrating Social Determinants of Health to Precision Medicine through Digital Transformation: An Exploratory Roadmap.

International journal of environmental research and public health
The COVID-19 pandemic has altered healthcare delivery platforms from traditional face-to-face formats to online care through digital tools. The healthcare industry saw a rapid adoption of digital collaborative tools to provide care to patients, regar...

Automatic vs. Human Recognition of Pain Intensity from Facial Expression on the X-ITE Pain Database.

Sensors (Basel, Switzerland)
Prior work on automated methods demonstrated that it is possible to recognize pain intensity from frontal faces in videos, while there is an assumption that humans are very adept at this task compared to machines. In this paper, we investigate whethe...

Generative adversarial network for glioblastoma ensures morphologic variations and improves diagnostic model for isocitrate dehydrogenase mutant type.

Scientific reports
Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether GAN ensures meaningful morphologic variations is still unknown. We investigated whether GAN-based synthetic images provide sufficient morphologic var...

Novel AI driven approach to classify infant motor functions.

Scientific reports
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA)...

Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time.

Scientific reports
Classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using har...

Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies.

Scientific reports
To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics features. Twenty-two patients with dermatomyositis (DM), 14 with amyopathic ...

COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images.

Scientific reports
Chest-X ray (CXR) radiography can be used as a first-line triage process for non-COVID-19 patients with pneumonia. However, the similarity between features of CXR images of COVID-19 and pneumonia caused by other infections makes the differential diag...