AIMC Topic: Humans

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Explaining electroencephalogram channel and subband sensitivity for alcoholism detection.

Computers in biology and medicine
Alcoholism, a progressive loss of control over alcohol consumption, deteriorates mental and physical health over time. Automatic alcoholism detection can aid in early interventions and timely corrective actions. For this purpose, electroencephalogram...

Humans take the visuospatial perspective of robots and objects that imply social presence.

Acta psychologica
Visual perspective-taking (VPT) plays a crucial role in social interactions. Although the mechanisms behind VPT have been thoroughly studied in human-human interactions, there are only a few studies examining whether humans can also adopt the visuosp...

From part to whole: AI-driven progress in fragment-based drug discovery.

Current opinion in structural biology
Fragment-based drug discovery is a technique that finds potent binding fragments to the binding hotspots and makes them a hit compound. The combination of fragments allows us to explore the large chemical space. Thus, it becomes an effective methodol...

AI for glaucoma, Are we reporting well? a systematic literature review of DECIDE-AI checklist adherence.

Eye (London, England)
BACKGROUND/OBJECTIVES: This systematic literature review examines the quality of early clinical evaluation of artificial intelligence (AI) decision support systems (DSS) reported in glaucoma care. Artificial Intelligence applications within glaucoma ...

Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques.

Magma (New York, N.Y.)
OBJECTIVE: Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed.

A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Neuroscience
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenagers across the globe. Neuroimaging and Machine Learning (ML) advancements have revolutionized its diagnosis and treatment approaches. Although, the rese...

T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment.

Journal of chemical information and modeling
There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to accurately predict the binding affinity of small molecules to a protein target in silico enables the...

A deep learning detection method for pancreatic cystic neoplasm based on Mamba architecture.

Journal of X-ray science and technology
OBJECTIVE: Early diagnosis of pancreatic cystic neoplasm (PCN) is crucial for patient survival. This study proposes M-YOLO, a novel model combining Mamba architecture and YOLO, to enhance the detection of pancreatic cystic tumors. The model addresses...

AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
BACKGROUND: AI-aided home stethoscopes offer the opportunity of continuous remote monitoring of cystic fibrosis (CF) patients, reducing the need for clinic visits.

Cooperative Magnetic Interfacial Microrobot Couple for Versatile Non-Contact Biomedical Applications.

Advanced materials (Deerfield Beach, Fla.)
Magnetic interfacial microrobots are increasingly recognized as a promising approach for potential biomedical applications ranging from electronic functionalization to minimally invasive surgery and targeted drug delivery. Nevertheless, existing rese...