AIMC Topic: Humans

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Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework.

Communications biology
Adverse Drug Reactions (ADRs) have a direct impact on human health. As continuous pharmacovigilance and drug monitoring prove to be costly and time-consuming, computational methods have emerged as promising alternatives. However, most existing comput...

Deep learning based on dynamic susceptibility contrast MR imaging for prediction of local progression in adult-type diffuse glioma (grade 4).

Scientific reports
Adult-type diffuse glioma (grade 4) has infiltrating nature, and therefore local progression is likely to occur within surrounding non-enhancing T2 hyperintense areas even after gross total resection of contrast-enhancing lesions. Cerebral blood volu...

Line-field confocal optical coherence tomography coupled with artificial intelligence algorithms to identify quantitative biomarkers of facial skin ageing.

Scientific reports
Quantitative biomarkers of facial skin ageing were studied from one hundred healthy Caucasian female volunteers, aged 20-70 years, using in vivo 3D Line-field Confocal Optical Coherence Tomography (LC-OCT) imaging coupled with Artificial Intelligence...

Perception, performance, and detectability of conversational artificial intelligence across 32 university courses.

Scientific reports
The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may...

Evaluation of AI Model for Cephalometric Landmark Classification (TG Dental).

Journal of medical systems
The accuracy of cephalometric landmark identification for malocclusion classification is essential for diagnosis and treatment planning. Identifying these landmarks is often complex and time-consuming for orthodontists. An AI model for classification...

An artificial intelligence-based pipeline for automated detection and localisation of epileptic sources from magnetoencephalography.

Journal of neural engineering
Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, an...

Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

PloS one
Even though the demand of head computed tomography (CT) in patients with mild traumatic brain injury (TBI) has progressively increased worldwide, only a small number of individuals have intracranial lesions that require neurosurgical intervention. As...

Segmenting white matter hyperintensities on isotropic three-dimensional Fluid Attenuated Inversion Recovery magnetic resonance images: Assessing deep learning tools on a Norwegian imaging database.

PloS one
An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particu...

Fuzzy entropy DEMATEL inference system for accurate and efficient cardiovascular disease diagnosis.

Computer methods in biomechanics and biomedical engineering
The global population is at risk from both communicable and non-communicable deadly diseases, including cardiovascular disease. Early detection and prevention of cardiovascular disease require an accurate self-detection model. Therefore, this study i...