AIMC Topic: Humans

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Can AI-generated faces serve as fillers in eyewitness lineups?

Memory (Hove, England)
To create a photo lineup for an eyewitness, police embed the suspect in a group of similar-looking individuals (i.e., fillers). If the witness selects the suspect from these photos of similar-looking people, then this provides evidence they remember ...

Intuitive Human-Artificial Intelligence Theranostic Complementarity.

Cancer biotherapy & radiopharmaceuticals
Deep learning artificial intelligence (AI) algorithms are poised to subsume diagnostic imaging specialists in radiology and nuclear medicine, where radiomics can consistently outperform human analysis and reporting capability, and do it faster, with ...

Artificial intelligence versus neurologists: A comparative study on multiple sclerosis expertise.

Clinical neurology and neurosurgery
INTRODUCTION: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting the central nervous system. MS diagnosis is complex, requiring magnetic resonance imaging and cerebrospinal fluid analysis due to the lack of definitive biomar...

Assessment of breast composition in MRI using artificial intelligence - A systematic review.

Radiography (London, England : 1995)
INTRODUCTION: Magnetic Resonance Imaging (MRI) performs a critical role in breast cancer diagnosis, especially for high-risk populations e.g. family history. MRI could take advantage of the implementation of artificial intelligence (AI). AI assessmen...

Advancing exposure science through artificial intelligence: Neural ordinary differential equations for predicting blood concentrations of volatile organic compounds.

Ecotoxicology and environmental safety
Volatile organic compounds (VOCs) are a significant concern for human health and environmental safety, requiring accurate models to predict their concentrations in body fluids for effective risk assessments. This study evaluates the application of ne...

Effect of Parallel Cognitive-Motor Training Tasks on Hemodynamic Responses in Robot-Assisted Rehabilitation.

Brain connectivity
Previous studies suggest that the combination of robot-assisted training with other concurrent tasks may promote the functional recovery and improvement better than the single task. It is well-established that robot-assisted rehabilitation training ...

Development of a Machine-Learning Algorithm to Identify Cauda Equina Compression on Magnetic Resonance Imaging Scans.

World neurosurgery
OBJECTIVE: Cauda equina syndrome (CES) poses significant neurological risks if untreated. Diagnosis relies on clinical and radiological features. As the symptoms are often nonspecific and common, the diagnosis is usually made after a magnetic resonan...

Ventricular Arrhythmia Classification Using Similarity Maps and Hierarchical Multi-Stream Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We address the problem of classification between ventricular tachycardia (VT), ventricular fibrillation (VF) and non-ventricular rhythms (NVR).

Robust Myocardial Perfusion MRI Quantification With DeepFermi.

IEEE transactions on bio-medical engineering
Stress perfusion cardiac magnetic resonance is an important technique for examining and assessing the blood supply of the myocardium. Currently, the majority of clinical perfusion scans are evaluated based on visual assessment by experienced clinicia...

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate From a Smartwatch.

IEEE transactions on bio-medical engineering
Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they of...