AIMC Topic: Humans

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AbAgym: a well-curated dataset for the mutational analysis of antibody-antigen complexes.

mAbs
With monoclonal antibodies becoming one of the largest classes of biopharmaceuticals, it is important to have curated data to train computational models that can accelerate their design. Despite the massive amount of mutagenesis data generated on ant...

Can artificial intelligence accurately predict the risk of hematoma expansion in intracerebral hemorrhage? A systematic review and Meta-analysis of 7,665 patients.

Neurosurgical review
Early prediction of hematoma expansion (HE) in patients with intracerebral hemorrhage (ICH) is critical for improving clinical outcome and guiding timely interventions. This study focuses on assessing the effectiveness of artificial intelligence (AI)...

Structural Heterogeneity of the Membrane-Interacting Region of the HIV-1 Envelope Glycoprotein.

Journal of the American Chemical Society
The HIV-1 envelope glycoprotein (Env) trimer (gp120/gp41) forms the key functional envelope spike and is the target of neutralizing antibodies. The glycoprotein gp41 component mediates the fusion of viral and host cell membranes. The membrane-interac...

[The role of artificial intelligence in the design and feasibility of early-phase oncology clinical trials].

Orvosi hetilap
Oncology clinical trials play a pivotal role in the development of new therapeutic options; however, their implementation remains an extremely costly and time-consuming process. Artificial intelligence can open new horizons in the design and conduct ...

Recent Advances in Oxidase-like Nanozymes: Mechanisms, Prediction Models, and Applications.

ACS applied materials & interfaces
Nanozymes, defined as nanomaterials exhibiting intrinsic enzyme-like catalytic properties, represent a rapidly expanding interdisciplinary frontier. Since the initial discovery of peroxidase-like nanozymes, a wide variety of nanomaterials have demons...

Novel insights into predicting the presence of micropapillary and solid components in stage IA lung adenocarcinoma using machine learning models of modifiable risk factors.

Annals of medicine
BACKGROUND: Lung adenocarcinoma (LUAC) patients with micropapillary (MP) and/or solid (S) generally demonstrate a poorer survival prognosis. In the diagnosis and treatment of stage IA LUAC, precisely establishing personalized treatment strategies for...

H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics.

International journal of health geographics
BACKGROUND: Mental-health geomatics require reliable ways to convert high-frequency GPS trajectories into meaningful place types that support indicators such as homestay, location entropy, and spatial extent of daily activities. Raw coordinates are t...

Research hotspots and trends of robotic rectal cancer surgery: a bibliometric analysis (2006-2025).

Journal of robotic surgery
Rectal cancer presents complex surgical challenges due to the confined pelvic anatomy. Robotic-assisted surgery has gained prominence for its enhanced precision, dexterity, and ergonomics compared to conventional laparoscopy. This bibliometric analys...

Computational Framework for Structuring and Analyzing Clinical Trial Criteria for AI-Guided Fine-grained Matching.

Journal of medical systems
While artificial intelligence (AI) has demonstrated potential in automating clinical trial matching, most existing solutions rely on high-level structured data or oversimplified criteria. This study introduces a framework to structure and analyze eli...

Targeting Ischemic Stroke with Neural Stem Cells: Insights into Endogenous Repair Mechanisms, Biomaterial-Based Delivery, and Exosome Therapies.

Molecular neurobiology
Neurological diseases, such as stroke, are typically deemed refractory because of the adult mammalian brain's poor ability to self-repair and regenerate, resulting in irreparable cellular damage. Neural stem cells (NSCs) have distinct capabilities to...