AIMC Topic: Male

Clear Filters Showing 24311 to 24320 of 27433 articles

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

Translational vision science & technology
PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, develop risk models to differentiate diabetic macular edema (DME), and predict anti-vascular endothelial growth factor (anti-VEGF) therapy response.

CNN-Based Device-Agnostic Feature Extraction From ONH OCT Scans.

Translational vision science & technology
PURPOSE: Optical coherence tomography (OCT)-derived measurements of the optic nerve head (ONH) from different devices are not interchangeable. This poses challenges to patient follow-up and collaborative studies. Here, we present a device-agnostic me...

Machine Learning-Based Detection of Bladder Cancer by Urine cfDNA Fragmentation Hotspots that Capture Cancer-Associated Molecular Features.

Clinical chemistry
BACKGROUND: cfDNA fragmentomics-based liquid biopsy is a potential option for noninvasive bladder cancer (BLCA) detection that remains an unmet clinical need.

[Clinical study of cervical lymph node metastasis in oral tongue squamous carcinoma by a machine learning model based on contrast-enhanced CT radiomics].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: To investigate the value of machine learning model based on enhanced CT imaging features and clinical parameters in predicting cervical lymph node metastasis in patients with tongue squamous cell carcinoma (TSCC).

Assessing diagnostic performance for common skin diseases using an AI-assisted tele-expertise platform: a proof of concept.

European journal of dermatology : EJD
Advancements in machine learning (ML) are making artificial intelligence more feasible in dermatology, with promising results for diagnosing skin cancers, though few studies cover common or inflammatory dermatoses. To evaluate the diagnostic accuracy...

A machine learning approach to predict HPV positivity of oropharyngeal squamous cell carcinoma.

Pathologica
HPV status is an important prognostic factor in oropharyngeal squamous cell carcinoma (OPSCC), with HPV-positive tumors associated with better overall survival. To determine HPV status, we rely on the immunohistochemical investigation for expression ...

Predicting apheresis yield and factors affecting peripheral blood stem cell harvesting using a machine learning model.

The Journal of international medical research
OBJECTIVE: Mobilization and collection of peripheral blood stem cells (PBSCs) are time-intensive and costly. Excessive apheresis sessions can cause physical discomfort for donors and increase the costs associated with collection. Therefore, it is ess...

Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT-Based Radiomic Features in Non-Small Cell Lung Cancer.

Cancer medicine
BACKGROUND: Non-small-cell lung cancer (NSCLC) remains a global health challenge, driving morbidity and mortality. The emerging field of radiogenomics utilizes statistical methods to correlate radiographic tumor features with genomic characteristics ...

Predictive Capacities of a Machine Learning Decision Tree Model Created to Analyse Feasibility of an Open or Robotic Kidney Transplant.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Machine learning has emerged as a potent tool in healthcare. A decision tree model was built to improve the decision-making process when determining the optimal choice between an open or robotic surgical approach for kidney transplant.

Stratification of Early Arrhythmic Risk in Patients Admitted for Acute Coronary Syndrome: The Role of the Machine Learning-Derived "PRAISE Score".

Clinical cardiology
BACKGROUND: The PRAISE (PRedicting with Artificial Intelligence riSk aftEr acute coronary syndrome) score is a machine learning-based model for predicting 1-year adverse cardiovascular or bleeding events in patients with acute coronary syndrome (ACS)...