AIMC Topic: Male

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Height prediction of individuals with osteogenesis imperfecta by machine learning.

Orphanet journal of rare diseases
BACKGROUND: Osteogenesis imperfecta (OI) is a genetic disorder characterized by low bone mass, bone fragility and short stature. There is a significant gap in knowledge regarding the growth patterns across different types of OI, and the prediction of...

Artificial Intelligence for Clinical Management of Male Infertility, a Scoping Review.

Current urology reports
PURPOSE OF REVIEW: Infertility impacts one in six couples worldwide, with male infertility contributing to approximately half of these cases. However, the causes of infertility remain incompletely understood, and current methods of clinical managemen...

Expression of Salivary miRNAs, Clinical, and Demographic Features in the Early Detection of Gastric Cancer: A Statistical and Machine Learning Analysis.

Journal of gastrointestinal cancer
OBJECTIVE: Gastric cancer ranks as one of the top five deadliest cancers worldwide and is often diagnosed at late stages. Analysis of saliva may provide a non-invasive approach for detection of malignancies in organs associated with the oral cavity. ...

Performance of expert fuzzy systems for prediction of rabbit feed intake after weaning.

Tropical animal health and production
The postweaning phase is stressful for rabbits due to maternal separation and the introduction of solid feed. Stress can be aggravated when animals are subjected to thermal discomfort. Therefore, thermal variables, such as air temperature, which infl...

QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals.

Scientific reports
The most cost-effective data collection method is electroencephalography (EEG), which obtains meaningful information about the brain. Therefore, EEG signal processing is crucial for neuroscience and machine learning (ML). Therefore, a new EEG stress ...

Machine Learning Approaches for the Fusion of Near-Infrared, Mid-Infrared, and Raman Data to Identify Cartilage Degradation in Human Osteochondral Plugs.

Applied spectroscopy
Vibrational spectroscopy methods such as mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopies have been shown to have great potential for in vivo biomedical applications, such as arthroscopic evaluation of joint injuries and degeneration...

Comparison of machine learning algorithms for automatic prediction of Alzheimer disease.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Alzheimer disease is a progressive neurological disorder marked by irreversible memory loss and cognitive decline. Traditional diagnostic tools, such as intracranial volume assessments, electroencephalography (EEG) signals, and brain magn...

Deep learning segmentation-based bone removal from computed tomography of the brain improves subdural hematoma detection.

Journal of neuroradiology = Journal de neuroradiologie
PURPOSE: Timely identification of intracranial blood products is clinically impactful, however the detection of subdural hematoma (SDH) on non-contrast CT scans of the head (NCCTH) is challenging given interference from the adjacent calvarium. This w...

Introduction and accuracy assessment of Nicolab's StrokeViewer in a developing stroke thrombectomy UK service. a service development/improvement project.

Clinical radiology
AIM: The aim of this study was to evaluate the implementation of artificial intelligence (AI) software in a quaternary stroke centre as well as assess the accuracy and efficacy of StrokeViewer software in large vessel occlusion detection and its pote...

Integrating radiomic and 3D autoencoder-based features for Non-Small Cell Lung Cancer survival analysis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The aim of this study is to develop a radiomic and deep learning-based signature for survival analysis of patients with Non-Small Cell Lung Cancer.