AIMC Topic: Humans

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Exploring geriatric nurses' perspectives on the adoption of AI in elderly care a qualitative study.

Geriatric nursing (New York, N.Y.)
This phenomenological study explored the perspectives of geriatric nurses on the adoption of artificial intelligence (AI) in elderly care. Thematic analysis of semi-structured interviews with 17 nurses revealed perceived benefits, challenges, ethical...

Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.

Journal of assisted reproduction and genetics
PURPOSE: Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics meth...

Role of artificial intelligence in early diagnosis and treatment of infectious diseases.

Infectious diseases (London, England)
Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificial Intelligence (AI) has emerged as a transformative force in healthcare, offering promising solution...

A Deep Learning-Based Approach to Characterize Skull Physical Properties: A Phantom Study.

Journal of biophotonics
Transcranial ultrasound imaging is a popular method to study cerebral functionality and diagnose brain injuries. However, the detected ultrasound signal is greatly distorted due to the aberration caused by the skull bone. The aberration mechanism mai...

Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant from whole genome sequencing and gene expression.

Antimicrobial agents and chemotherapy
Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susce...

Strategic partnerships for AI-driven drug discovery: The role of relational dynamics.

Drug discovery today
Artificial intelligence-driven drug discovery (AIDD) companies hold significant promise for transforming pharmaceutical development, yet little is known about how they manage partnerships with established pharmaceutical firms. To address this researc...

Extracting social determinants of health from inpatient electronic medical records using natural language processing.

Journal of epidemiology and population health
BACKGROUND: Social determinants of health (SDOH) have been shown to be important predictors of health outcomes. Here we developed methods to extract them from inpatient electronic medical record (EMR) data using techniques compatible with current EMR...

Prognostic Significance and Associations of Neural Network-Derived Electrocardiographic Features.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. ...

Deep Learning to Detect Pulmonary Hypertension from the Chest X-Ray Images of Patients with Systemic Sclerosis.

International heart journal
Pulmonary hypertension (PH) is a serious prognostic complication in patients with systemic sclerosis (SSc). Deep learning models can be applied to detect PH in the chest X-ray images of these patients. The aim of the study was to investigate the perf...