AIMC Topic: Female

Clear Filters Showing 23741 to 23750 of 29210 articles

Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa.

Journal of clinical pathology
BACKGROUND: Deep learning (DL) models are effective pre-screening tools for detecting mismatch repair deficiency (dMMR) in colorectal carcinoma (CRC). These models have been trained and validated on large cohorts from the Northern Hemisphere, without...

Do We Still Need Randomized Controlled Trials to Support Use of New Methods of Breast Cancer Screening?

Journal of breast imaging
Randomized controlled trials (RCTs) have confirmed the mortality benefits of screening mammography and are the gold standard for evaluating new diagnostic tests and medical interventions. Reliable and rigorous execution of RCTs can be complex and req...

Artificial intelligence-based identification of thin-cap fibroatheromas and clinical outcomes: the PECTUS-AI study.

European heart journal
BACKGROUND AND AIMS: Coronary thin-cap fibroatheromas (TCFA) are associated with adverse outcome, but identification of TCFA requires expertise and is highly time-demanding. This study evaluated the utility of artificial intelligence (AI) for TCFA id...

Sex-specific body fat distribution predicts cardiovascular ageing.

European heart journal
BACKGROUND AND AIMS: Cardiovascular ageing is a progressive loss of physiological reserve, modified by environmental and genetic risk factors, that contributes to multi-morbidity due to accumulated damage across diverse cell types, tissues, and organ...

Diagnosis of uterine diseases by label-free serum SERS fingerprints with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Early detection of uterine diseases is critically important for women's reproductive health. Here, we propose a novel and robust serum-based SERS analysis platform that integrates machine learning algorithms. This is the first application of it in th...

Combined magnetic resonance imaging and serum analysis reveals distinct multiple sclerosis types.

Brain : a journal of neurology
Multiple sclerosis (MS) is a highly heterogeneous disease in its clinical manifestation and progression. Predicting individual disease courses is key for aligning treatments with underlying pathobiology. We developed an unsupervised machine learning ...

Comparative effectiveness of anti-seizure medications in emulated trials using medical informatics.

Brain : a journal of neurology
Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar sequence for many patients. Comparative effectiveness data beyond the first ASM prescription are limited. Artificial intelligence can automatically e...

Photon-Counting Detector CT of the Brain Reduces Variability of Hounsfield Units and Has a Mean Offset Compared with Energy-Integrating Detector CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Distinguishing GM from WM is essential for CT of the brain. The recently established photon-counting detector (PCD)-CT technology uses a novel detection technique that might allow more precise measurement of tissue attenuation...

Deep Learning-Based Prediction of PET Amyloid Status Using MRI.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Identifying amyloid-beta (Aβ)-positive patients is essential for Alzheimer disease clinical trials and disease-modifying treatments but currently requires PET or CSF sampling. Previous MRI-based deep learning models using only...