AIMC Topic: Databases, Factual

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Artificial intelligence model for tumoral clinical decision support systems.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Comparative diagnostic in brain tumor evaluation makes possible to use the available information of a medical center to compare similar cases when a new patient is evaluated. By leveraging Artificial Intelligence models, the...

Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights.

Respiratory research
The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pre...

DMA-HPCNet: Dual Multi-Level Attention Hybrid Pyramid Convolution Neural Network for Alzheimer's Disease Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Computer-aided diagnosis (CAD) plays a crucial role in the clinical application of Alzheimer's disease (AD). In particular, convolutional neural network (CNN)-based methods are highly sensitive to subtle changes caused by brain atrophy in medical ima...

Enhancing the coverage of SemRep using a relation classification approach.

Journal of biomedical informatics
OBJECTIVE: Relation extraction is an essential task in the field of biomedical literature mining and offers significant benefits for various downstream applications, including database curation, drug repurposing, and literature-based discovery. The b...

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.

BMC musculoskeletal disorders
BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperatively anticipate adverse postoperative outcomes given the procedure's expanding use. Our study aims to ...

MRIO: the Magnetic Resonance Imaging Acquisition and Analysis Ontology.

Neuroinformatics
Magnetic resonance imaging of the brain is a useful tool in both the clinic and research settings, aiding in the diagnosis and treatments of neurological disease and expanding our knowledge of the brain. However, there are many challenges inherent in...

Impact of an artificial intelligence based model to predict non-transplantable recurrence among patients with hepatocellular carcinoma.

HPB : the official journal of the International Hepato Pancreato Biliary Association
OBJECTIVE: We sought to develop Artificial Intelligence (AI) based models to predict non-transplantable recurrence (NTR) of hepatocellular carcinoma (HCC) following hepatic resection (HR).

Machine learning prediction of hospitalization costs for coronary artery bypass grafting operations.

Surgery
BACKGROUND: With the steady rise in health care expenditures, the examination of factors that may influence the costs of care has garnered much attention. Although machine learning models have previously been applied in health economics, their applic...

ADHD classification with cross-dataset feature selection for biomarker consistency detection.

Journal of neural engineering
Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children. While numerous intelligent methods are applied for its subjective diagnosis, they seldom consider the consistency problem of ADHD biomarkers. In p...

Artificial Intelligence for Urology Research: The Holy Grail of Data Science or Pandora's Box of Misinformation?

Journal of endourology
Artificial intelligence tools such as the large language models (LLMs) Bard and ChatGPT have generated significant research interest. Utilization of these LLMs to study the epidemiology of a target population could benefit urologists. We investigate...