OBJECTIVE: To develop a probabilistic model for discovering and quantifying determinants of outbreak detection and to use the model to predict detection performance for new outbreaks.
BACKGROUND: International Classification of Diseases (ICD) codes utilized for congenital heart defect (CHD) case identification in datasets have substantial false-positive (FP) rates. Incorporating machine learning (ML) algorithms following case sele...
Mathematical biosciences and engineering : MBE
Dec 11, 2024
The hippocampus is a small, yet intricate seahorse-shaped tiny structure located deep within the brain's medial temporal lobe. It is a crucial component of the limbic system, which is responsible for regulating emotions, memory, and spatial navigatio...
Purpose To evaluate the ability of a semiautonomous artificial intelligence (AI) model to identify screening mammograms not suspicious for breast cancer and reduce the number of false-positive examinations. Materials and Methods The deep learning alg...
OBJECTIVE: To determine the diagnostic accuracy of a deep-learning (DL)-based algorithm using chest computed tomography (CT) scans for the rapid diagnosis of coronavirus disease 2019 (COVID-19), as compared to the reference standard reverse-transcrip...
Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably hig...
Technology in cancer research & treatment
Jan 1, 2021
Signet ring cell carcinoma (SRCC) of the stomach is a rare type of cancer with a slowly rising incidence. It tends to be more difficult to detect by pathologists, mainly due to its cellular morphology and diffuse invasion manner, and it has poor prog...
American journal of clinical pathology
Jul 7, 2020
OBJECTIVES: Preanalytical factors, such as hemolysis, affect many components of a test panel. Machine learning can be used to recognize these patterns, alerting clinicians and laboratories to potentially erroneous results. In particular, machine lear...
BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories r...