Identify biological Alzheimer's disease using a novel nucleic acid-linked protein immunoassay.

Blood-based biomarkers have been revolutionizing the detection, diagnosis and screening of Alzheimer's disease. Specifically, phosphorylated-tau variants (p-tau, p-tau and p-tau) are promising biomarkers for identifying Alzheimer's disease pathology. Antibody-based assays such as single molecule arrays immunoassays are powerful tools to investigate pathological changes indicated by blood-based biomarkers and have been studied extensively in the Alzheimer's disease research field.

High Rates of Unnecessary Surgery for Indeterminate Thyroid Nodules in the Absence of Molecular Test and the Cost-Effectiveness of Utilizing Molecular Test in an Asian Population: A Decision Analysis.

Cytologically indeterminate thyroid nodules (Bethesda class III or IV) carry a 10-40% risk of malignancy. Diagnostic lobectomies are frequently performed but negative surgeries incur unnecessary costs on the healthcare system, potential complications, and negative impacts on quality of life. Molecular tests (MTs) have been developed to reduce unnecessary surgeries.

Ruptured: Retrospective Analysis Undertaken for Patients Treated for Unexplained Retroperitoneal or Abdominal Pain in the Emergency Department.

Symptomatic abdominal aortic aneurysms carry significant mortality risk. This is supplemented by the Royal College of Emergency Medicine guidelines which suggest imaging for patients 50 years of age or older presenting with unexplained abdominal, flank, or back pain. This study aimed to evaluate the prevalence and mortality rates of patients with symptomatic abdominal aortic aneurysms in a high-risk population and to assess scanning rates in the accident and emergency department.

Glaucoma detection and staging from visual field images using machine learning techniques.

Purpose: In this study, we investigated the performance of deep learning (DL) models to differentiate between normal and glaucomatous visual fields (VFs) and classify glaucoma from early to the advanced stage to observe if the DL model can stage glaucoma as Mills criteria using only the pattern deviation (PD) plots. The DL model results were compared with a machine learning (ML) classifier trained on conventional VF parameters.

Methods: A total of 265 PD plots and 265 numerical datasets of Humphrey 24-2 VF images were collected from 119 normal and 146 glaucomatous eyes to train the DL models to classify the images into four groups: normal, early glaucoma, moderate glaucoma, and advanced glaucoma.