AIMC Topic: Female
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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
Jun 11, 2025
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
Jun 11, 2025
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...
Academic Medical Centers
Natural Language Processing
Emergency Service, Hospital
Stroke
Data Mining
Risk Factors
Aged
Aged, 80 and over
Male
Middle Aged
Risk Assessment
Time Factors
Predictive Value of Tests
Retrospective Studies
Electronic Health Records
Female
Reproducibility of Results
Humans
Prognosis
Soft-tissue prediction based on 3D photographs for virtual surgery planning of orthognathic surgery.
Computers in biology and medicine
Jun 11, 2025
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...
AI-empowered health coaching for university students: A mixed-method process evaluation.
Computers in biology and medicine
Jun 11, 2025
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...
Identifying patients at risk of increased health utilization following lumbar spine surgery.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jun 11, 2025
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...
Split DNA Tetrahedron-Mediated Spatiotemporal-Hierarchy CRISPR Cascade Integrated with Au@Pt Nanolabels and Artificial Intelligence for a Cervical Cancer MicroRNA Bioassay.
ACS nano
Jun 11, 2025
The screening and monitoring of microRNAs as cancer molecular biomarkers is clinically significant, but traditional methods lack sufficient sensitivity, accuracy, and convenience. The CRISPR-colorimetric lateral flow assay (CLFA) integration offers a...
A lipid atlas of the human kidney.
Science advances
Jun 11, 2025
Tissue atlases provide foundational knowledge on the cellular organization and molecular distributions across molecular classes and spatial scales. Here, we construct a comprehensive spatiomolecular lipid atlas of the human kidney from 29 donor tissu...
Diagnostic accuracy of machine learning-based magnetic resonance imaging models in breast cancer classification: a systematic review and meta-analysis.
World journal of surgical oncology
Jun 11, 2025
OBJECTIVE: This meta-analysis evaluates the diagnostic accuracy of machine learning (ML)-based magnetic resonance imaging (MRI) models in distinguishing benign from malignant breast lesions and explores factors influencing their performance.
Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: Observational Cohort Study.
Journal of medical Internet research
Jun 11, 2025
BACKGROUND: Implementing machine learning models to identify clinical deterioration in the wards is associated with decreased morbidity and mortality. However, these models have high false positive rates and only use structured data.
28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.
Clinical and experimental medicine
Jun 11, 2025
To develop and validate a machine learning prediction model for 28-day all-cause mortality in patients with alcoholic cirrhosis using data from the MIMIC-IV database. The data of 2134 patients diagnosed with alcoholic cirrhosis (AC) were obtained fro...
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