AIMC Topic: Humans

Clear Filters Showing 6641 to 6650 of 95995 articles

A two-stage machine learning-based risk assessment model for intravenous thrombolysis in acute ischemic stroke (AIS): A multi-center modeling study of pooled datasets.

International journal of medical informatics
OBJECTIVE: Develop a two-stage, machine learning-based thrombolysis risk stratification model from existing medical datasets and electronic health records to predict the risk of early hemorrhagic transformation(HT) and in-hospital mortality(IM) follo...

Enhancing rare disease detection with deep phenotyping from EHR narratives: evaluation on Jeune syndrome.

International journal of medical informatics
BACKGROUND: Patients with rare diseases frequently experience misdiagnoses and long diagnostic delays. Accelerating their diagnosis is essential to ensure timely access to appropriate care. Given the increasing availability of EHRs, combining artific...

SmartAlert: Machine learning-based patient-ventilator asynchrony detection system in intensive care units.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Patient-ventilator asynchronies (PVA) are associated with ventilator-induced lung injury and increased mortality. Current detection methods rely on static thresholds, extensive preprocessing, or proprietary ventilator data. ...

Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach.

Psychiatry research
Adolescents are vulnerable to experiencing problematic gambling, although its prevalence and potential risk factors vary across countries. This study aims to identify cross-jurisdictional factors associated with higher gambling frequency among adoles...

Predictive modeling of postoperative hyponatremia after pituitary adenoma surgery.

Clinical neurology and neurosurgery
OBJECTIVE: To improve the prediction of postoperative hyponatremia after pituitary surgery by comparing six machine learning (ML) models.

Stabilizing machine learning for reproducible and explainable results: A novel validation approach to subject-specific insights.

Computer methods and programs in biomedicine
INTRODUCTION: Machine Learning (ML) is transforming medical research by enhancing diagnostic accuracy, predicting disease progression, and personalizing treatments. While general models trained on large datasets identify broad patterns across populat...

A multimodal skin lesion classification through cross-attention fusion and collaborative edge computing.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Skin cancer is a significant global health concern requiring early and accurate diagnosis to improve patient outcomes. While deep learning-based computer-aided diagnosis (CAD) systems have emerged as effective diagnostic support tools, they often fac...

Advancing AI-driven surveillance systems in hospital: A fine-grained instance segmentation dataset for accurate in-bed patient monitoring.

Computers in biology and medicine
In the era of digital health, artificial intelligence (AI)-driven patient monitoring systems have attracted growing interest for their potential to prevent accidents in clinical settings. However, the advancement of these systems requires the availab...

Innovative AI models for clinical decision-making: predicting blastocyst formation and quality from time-lapse embryo images up to embryonic day 3.

Computers in biology and medicine
Accurate embryo assessment on embryonic day 3 of assisted reproductive technology (ART) is crucial for deciding whether to continue the culture until day 5 (blastocyst stage) or opt for earlier transfer or cryopreservation. Prolonged culture often im...

Medical application of deep-learning-based head pose estimation from RGB image sequence.

Computers in biology and medicine
Recently, telemedicine has allowed doctor-to-patient or doctor-to-doctor consultations to tackle traditional problems: the COVID-19 pandemic, remote areas, long-time usage per visit, and dependence on family members in transportation. Nevertheless, f...