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Artificial Intelligence Driven Prehospital ECG Interpretation for the Reduction of False Positive Emergent Cardiac Catheterization Lab Activations: A Retrospective Cohort Study.
Prehospital emergency care
Sep 12, 2024
OBJECTIVES: Data suggest patients suffering acute coronary occlusion myocardial infarction (OMI) benefit from prompt primary percutaneous intervention (PPCI). Many emergency medical services (EMS) activate catheterization labs to reduce time to PPCI,...
Machine Learning-Based Prediction of Chronic Shunt-Dependent Hydrocephalus After Spontaneous Subarachnoid Hemorrhage.
World neurosurgery
Sep 12, 2024
BACKGROUND: Chronic posthemorrhagic hydrocephalus often arises following spontaneous subarachnoid hemorrhage (SAH). Timely identification of patients predisposed to develop chronic shunt-dependent hydrocephalus may significantly enhance clinical outc...
Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation.
Journal of cardiovascular medicine (Hagerstown, Md.)
Sep 12, 2024
BACKGROUND: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive and therapeutic strategies. In this study, we developed and evaluated an image-based electrocardiogram (ECG) analyzing an artificial intelligence (AI...
Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.
Journal of clinical microbiology
Sep 12, 2024
Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evalu...
An artificial intelligence-based model exploiting H&E images to predict recurrence in negative sentinel lymph-node melanoma patients.
Journal of translational medicine
Sep 12, 2024
BACKGROUND: Risk stratification and treatment benefit prediction models are urgent to improve negative sentinel lymph node (SLN-) melanoma patient selection, thus avoiding costly and toxic treatments in patients at low risk of recurrence. To this end...
The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery.
Biomedical engineering online
Sep 12, 2024
BACKGROUND: Anomalous origin of coronary artery is a common coronary artery anatomy anomaly. The anomalous origin of the coronary artery may lead to problems such as narrowing of the coronary arteries at the beginning of the coronary arteries and abn...
Mild cognitive impairment prediction based on multi-stream convolutional neural networks.
BMC bioinformatics
Sep 12, 2024
BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Cur...
Training and validation of a deep learning U-net architecture general model for automated segmentation of inner ear from CT.
European radiology experimental
Sep 12, 2024
BACKGROUND: The intricate three-dimensional anatomy of the inner ear presents significant challenges in diagnostic procedures and critical surgical interventions. Recent advancements in deep learning (DL), particularly convolutional neural networks (...
Integrating respiratory microbiome and host immune response through machine learning for respiratory tract infection diagnosis.
NPJ biofilms and microbiomes
Sep 12, 2024
At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is an urgent need for better diagnostic methods. This study enrolled 136 patients from 2020 to 2021 and collected bronchoalveolar lavage fluid (BALF) spec...
Development and evaluation of a model for predicting the risk of healthcare-associated infections in patients admitted to intensive care units.
Frontiers in public health
Sep 12, 2024
This retrospective study used 10 machine learning algorithms to predict the risk of healthcare-associated infections (HAIs) in patients admitted to intensive care units (ICUs). A total of 2,517 patients treated in the ICU of a tertiary hospital in Ch...
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