AIMC Topic: Female

Clear Filters Showing 8431 to 8440 of 29210 articles

Comparison of Manual vs Artificial Intelligence-Based Muscle MRI Segmentation for Evaluating Disease Progression in Patients With CMT1A.

Neurology
BACKGROUND AND OBJECTIVES: Intramuscular fat fraction (FF), assessed with quantitative MRI (qMRI), has emerged as one of the few responsive outcome measures in CMT1A patients. The main limitation for its use in future therapeutic trials is the time r...

Use of Deep Learning to Identify Peripheral Arterial Disease Cases From Narrative Clinical Notes.

The Journal of surgical research
INTRODUCTION: Peripheral arterial disease (PAD) is the leading cause of amputation in the United States. Despite affecting 8.5 million Americans and more than 200 million people globally, there are significant gaps in awareness by both patients and p...

Using Atrial Fibrillation Burden Trends and Machine Learning to Predict Near-Term Risk of Cardiovascular Hospitalization.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Atrial fibrillation is associated with an increased risk of cardiovascular hospitalization (CVH), which may be triggered by changes in daily burden. Machine learning of dynamic trends in atrial fibrillation burden, as measured by insertab...

Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm.

Pathogens (Basel, Switzerland)
Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strategy in 2035. A descriptive, retrospective review of medical records of patients, who were diagnosed wi...

Predicting Breast Cancer Relapse from Histopathological Images with Ensemble Machine Learning Models.

Current oncology (Toronto, Ont.)
Relapse and metastasis occur in 30-40% of breast cancer patients, even after targeted treatments like trastuzumab for HER2-positive breast cancer. Accurate individual prognosis is essential for determining appropriate adjuvant treatment and early int...

A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine.

PloS one
BACKGROUND: In Persian medicine, early diagnosis and treatment of stomach dystemperament is crucial for preventing other diseases. However, traditional medicine diagnosis often involves ambiguous and less structured information making it challenging ...

Can deep learning identify humans by automatically constructing a database with dental panoramic radiographs?

PloS one
The aim of this study was to propose a novel method to identify individuals by recognizing dentition change, along with human identification process using deep learning. Recent and past images of adults aged 20-49 years with more than two dental pano...

Ensemble approach for predicting the diagnosis of osteoarthritis using physical activity factors.

Journal of evaluation in clinical practice
BACKGROUND: Osteoarthritis (OA) is a common degenerative disease of the joints. Risk factors for OA include non-modifiable factors such as age and sex, as well as modifiable factors like physical activity.

Deep Learning Segmentation of Chromogenic Dye RNAscope From Breast Cancer Tissue.

Journal of imaging informatics in medicine
RNAscope staining of breast cancer tissue allows pathologists to deduce genetic characteristics of the cancer by inspection at the microscopic level, which can lead to better diagnosis and treatment. Chromogenic RNAscope staining is easy to fit into ...

Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance.

European radiology
OBJECTIVES: To compare standard-resolution balanced steady-state free precession (bSSFP) cine images with cine images acquired at low resolution but reconstructed with a deep learning (DL) super-resolution algorithm.