AIMC Topic: Humans

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Machine learning analysis of serum cholesterol's impact on knee osteoarthritis progression.

Scientific reports
The controversy surrounding whether serum total cholesterol is a risk factor for the graded progression of knee osteoarthritis (KOA) has prompted this study to develop an authentic prediction model using a machine learning (ML) algorithm. The objecti...

Development and performance evaluation of fully automated deep learning-based models for myocardial segmentation on T1 mapping MRI data.

Scientific reports
To develop a deep learning-based model capable of segmenting the left ventricular (LV) myocardium on native T1 maps from cardiac MRI in both long-axis and short-axis orientations. Models were trained on native myocardial T1 maps from 50 healthy volun...

Segmentation of ovarian cyst in ultrasound images using AdaResU-net with optimization algorithm and deep learning model.

Scientific reports
Ovarian cysts pose significant health risks including torsion, infertility, and cancer, necessitating rapid and accurate diagnosis. Ultrasonography is commonly employed for screening, yet its effectiveness is hindered by challenges like weak contrast...

C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning.

Scientific reports
The rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation o...

Optimization of diabetes prediction methods based on combinatorial balancing algorithm.

Nutrition & diabetes
BACKGROUND: Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction. This imbalance often results in...

Impact of Gold-Standard Label Errors on Evaluating Performance of Deep Learning Models in Diabetic Retinopathy Screening: Nationwide Real-World Validation Study.

Journal of medical Internet research
BACKGROUND: For medical artificial intelligence (AI) training and validation, human expert labels are considered the gold standard that represents the correct answers or desired outputs for a given data set. These labels serve as a reference or bench...

Cancer Prevention and Treatment on Chinese Social Media: Machine Learning-Based Content Analysis Study.

Journal of medical Internet research
BACKGROUND: Nowadays, social media plays a crucial role in disseminating information about cancer prevention and treatment. A growing body of research has focused on assessing access and communication effects of cancer information on social media. Ho...

Characterizing the Adoption and Experiences of Users of Artificial Intelligence-Generated Health Information in the United States: Cross-Sectional Questionnaire Study.

Journal of medical Internet research
BACKGROUND: OpenAI's ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outc...

Advancing aneurysm management: the potential of AI and machine learning in enhancing safety and predictive accuracy.

Neurosurgical review
Cerebral aneurysm rupture, the predominant cause of non-traumatic subarachnoid hemorrhage, underscores the need for effective treatment and early detection methods. A study in Neurosurgical Review compared microsurgical clipping to endovascular thera...

Wasserstein generative adversarial network with gradient penalty and convolutional neural network based motor imagery EEG classification.

Journal of neural engineering
Due to the difficulty in acquiring motor imagery electroencephalography (MI-EEG) data and ensuring its quality, insufficient training data often leads to overfitting and inadequate generalization capabilities of deep learning-based classification net...