AIMC Topic: Humans

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The Role of AI-driven Volumetric Aneurysm Analysis in the Management of Cerebral Aneurysms.

Neuroimaging clinics of North America
This article looks at the current state of aneurysm risk modeling, exploring the limitations of linear measurement. It reviews articles using Food and Drug Administration (FDA)-approved artificial intelligence-driven volumetric measurement tools both...

Evaluation of semi-automated versus fully automated technologies for computed tomography scalable body composition analyses in patients with severe acute respiratory syndrome Coronavirus-2.

Clinical nutrition ESPEN
RATIONALE AND OBJECTIVES: Fully automated, artificial intelligence (AI) -based software has recently become available for scalable body composition analysis. Prior to broad application in the clinical arena, validation studies are needed. Our goal wa...

Identification of neurological text markers associated with risk of stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...

Soft-tissue prediction based on 3D photographs for virtual surgery planning of orthognathic surgery.

Computers in biology and medicine
OBJECTIVES: In orthognathic surgery, preoperative three-dimensional soft-tissue simulations are frequently used to determine the desired jaw displacements to enhance the facial soft tissue. This study aimed to develop and validate a deep learning-bas...

Enhancing drug-drug interaction classification by leveraging textual drug arguments.

Computers in biology and medicine
BACKGROUND: The accurate identification and classification of drug-drug interactions (DDIs) are critical for ensuring patient safety and optimizing treatment outcomes in modern healthcare. Traditional methods for DDI classification primarily focus on...

Implementation of biomedical segmentation for brain tumor utilizing an adapted U-net model.

Computers in biology and medicine
Using radio signals from a magnetic field, magnetic resonance imaging (MRI) represents a medical procedure that produces images to provide more information than typical scans. Diagnosing brain tumors from MRI is difficult because of the wide range of...

AI-empowered health coaching for university students: A mixed-method process evaluation.

Computers in biology and medicine
BACKGROUND: Artificial Intelligence (AI)-empowered health coaching (HC) has the potential to enhance HC effectiveness by providing real-time, evidence-based support. However, integrating AI into live HC sessions presents challenges, particularly in r...

Towards more reliable prostate cancer detection: Incorporating clinical data and uncertainty in MRI deep learning.

Computers in biology and medicine
Prostate cancer (PCa) is one of the most common cancers among men, and artificial intelligence (AI) is emerging as a promising tool to enhance its diagnosis. This work proposes a classification approach for PCa cases using deep learning techniques. W...

Identifying patients at risk of increased health utilization following lumbar spine surgery.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: Adequate preoperative identification of patients at risk of significant healthcare utilization after surgery could help guide preoperative decision-making as well as postoperative patient management. While several studies have proposed me...

Automated identification of serotype using MALDI-TOF mass spectrometry and machine learning techniques.

Journal of clinical microbiology
UNLABELLED: serotyping is essential for epidemiological studies and clinical treatment guidance. However, traditional serological agglutination methods are time-consuming, technically complex, and difficult to adopt at scale. Matrix-assisted laser d...