Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The models achieved high sensitivity and specificity among ...
Objective Chronic kidney disease (CKD) arises due to uncontrolled hypertension (HTN). HTN significantly increases the risk of complications in vital organs, mainly the kidneys. If hypertensive ...
This population-based study used plasma pTau217 to estimate how common Alzheimer’s disease neuropathological changes are across age and cognitive status in a Norwegian community cohort. Prevalence ...
Surgical site infections (SSIs), particularly intra-abdominal (IAB) infections, are challenging to identify and remain a ...
Introduction: ST-segment elevation myocardial infarction (STEMI) is one of the major subtypes of acute coronary syndrome, with rapid progression and a high risk of death and disability. Although some ...
Google Ads has introduced a new metric — “Conv. value (incl. predicted)” — without any official announcement or documentation, sparking curiosity among advertisers. Why it matters This subtle addition ...
Have you ever been prospecting and wished you could read minds to know exactly who’s ready to sell? While telepathy isn’t an option, predictive analytics will get you pretty close. Predictive ...
Prostate Imaging Reporting and Data System (PIRADS) v2.1 scoring with multiparametric MRI (mpMRI) has a pooled 90% negative predictive value (NPV). PSA density (PSAD) ≤0.15ng/ml/cm3 has been shown to ...
Objectives This study aimed to develop and validate a machine-learning (ML) model to predict iron deficiency without anaemia (IDWA) using routinely collected electronic health record (EHR) data. The ...
The battlefield of 2030 will be characterized by increased complexity, uncertainty, lethality, and technological advancements, requiring seamless sustainment across all domains. The proliferation of ...
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