AIMC Topic: Humans

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Operationalizing postmortem pathology-MRI association studies in Alzheimer's disease and related disorders with MRI-guided histology sampling.

Acta neuropathologica communications
Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling that may miss critical areas affected by Alzheimer's disease and related disorders. Ultra-high reso...

Comparing orthodontic pre-treatment information provided by large language models.

BMC oral health
This study collected and screened the 50 most common pre-treatment consultation questions from adult orthodontic patients through clinical practice. Responses to these questions were generated using three large language models: Ernie Bot, ChatGPT, an...

Single-cell data combined with phenotypes improves variant interpretation.

BMC genomics
BACKGROUND: Whole genome sequencing offers significant potential to improve the diagnosis and treatment of rare diseases by enabling the identification of thousands of rare, potentially pathogenic variants. Existing variant prioritisation tools can b...

Performance of a novel multimodal large language model in ınterpreting meibomian glands quantitatively and qualitatively.

International ophthalmology
PURPOSE: To evaluate the performance of a multimodal large language model (LLM), Claude 3.5 Sonnet, in interpreting meibography images for Meibomian gland dropout grading and morphological abnormality detection.

Personalized prediction of gait freezing using dynamic mode decomposition.

Scientific reports
Freezing of gait (FoG) is a common severe gait disorder in patients with advanced Parkinson's disease. The ability to predict the onset of FoG episodes early on allows for timely intervention, which is essential for improving the life quality of pati...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Scientific reports
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative, or missingness) in binary categorical variables in electronic medical records (EMRs) using propens...

Drug-drug interaction prediction of traditional Chinese medicine based on graph attention networks.

Scientific reports
Predicting drug-drug interactions (DDI) is crucial for preventing adverse reactions in patients and plays a vital role in drug design and development. However, traditional Chinese medicine (TCM) formulations, typically composed of multiple herbal ing...

MicroRNA signature predicts post operative atrial fibrillation after coronary artery bypass grafting.

Scientific reports
Early detection of atrial fibrillation (AFib) is crucial for altering its natural progression and complication profile. Traditional demographic and lifestyle factors often fail as predictors of AFib. This study investigated pre-operative, circulating...

C2 pars interarticularis length on the side of high-riding vertebral artery with implications for pars screw insertion.

Scientific reports
C2 pars interarticularis length (C2PIL) required for pars screws has not been thoroughly studied in subjects with high-riding vertebral artery (HRVA). We aimed to measure C2PIL specifically on the sides with HRVA, define short pars, optimal pars scre...

A Benchmark for Virus Infection Reporter Virtual Staining in Fluorescence and Brightfield Microscopy.

Scientific data
Detecting virus-infected cells in light microscopy requires a reporter signal commonly achieved by immunohistochemistry or genetic engineering. While classification-based machine learning approaches to the detection of virus-infected cells have been ...