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Health consumers' ethical concerns towards artificial intelligence in Australian emergency departments.
Emergency medicine Australasia : EMA
Jun 18, 2024
OBJECTIVES: To investigate health consumers' ethical concerns towards the use of artificial intelligence (AI) in EDs.
Correlation of limited-early-response status with 12-month CST, BVA, and machine learning-quantified retinal fluid in diabetic macular oedema in routine clinical practice.
Eye (London, England)
Jun 18, 2024
BACKGROUND/OBJECTIVES: Anti-VEGF treatment response in DMO has been measured by changes in the central subfield thickness (CST) and best visual acuity (BVA) outcomes at 3 months after initial treatment, termed early or limited early response (ER/LER)...
Rapid Electroencephalography and Artificial Intelligence in the Detection and Management of Nonconvulsive Seizures.
Annals of emergency medicine
Jun 18, 2024
STUDY OBJECTIVE: Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental status. This study assessed nonconvulsive status epilepticus prevalence in emergency department (ED) patients with acute neurologic presentations using...
A pretreatment multiparametric MRI-based radiomics-clinical machine learning model for predicting radiation-induced temporal lobe injury in patients with nasopharyngeal carcinoma.
Head & neck
Jun 18, 2024
BACKGROUND: To establish and validate a machine learning model using pretreatment multiparametric magnetic resonance imaging-based radiomics data with clinical data to predict radiation-induced temporal lobe injury (RTLI) in patients with nasopharyng...
A new methodology for determining the central pressure waveform from peripheral measurement using Fourier-based machine learning.
Artificial intelligence in medicine
Jun 18, 2024
Radial applanation tonometry is a well-established technique for hemodynamic monitoring and is becoming popular in affordable non-invasive wearable healthcare electronics. To assess the central aortic pressure using radial-based measurements, there i...
Small sized centroblasts as poor prognostic factor in follicular lymphoma - Based on artificial intelligence analysis.
Computers in biology and medicine
Jun 18, 2024
Histological assessment of centroblasts is an important evaluation in the diagnosis of follicular lymphoma, but there is substantial observer variation in assessment among hematopathologists. We aimed to perform quantitative morphological analysis of...
Association of Cardiovascular Health With Brain Age Estimated Using Machine Learning Methods in Middle-Aged and Older Adults.
Neurology
Jun 18, 2024
BACKGROUND AND OBJECTIVES: Cardiovascular health (CVH) has been associated with cognitive decline and dementia, but the extent to which CVH affects brain health remains unclear. We investigated the association of CVH, assessed using Life's Essential ...
Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model.
Biomedical engineering online
Jun 18, 2024
OBJECTIVES: This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC).
An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.
Respiratory research
Jun 18, 2024
BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-ba...
Digital telomere measurement by long-read sequencing distinguishes healthy aging from disease.
Nature communications
Jun 18, 2024
Telomere length is an important biomarker of organismal aging and cellular replicative potential, but existing measurement methods are limited in resolution and accuracy. Here, we deploy digital telomere measurement (DTM) by nanopore sequencing to un...
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