AIMC Topic: Female

Clear Filters Showing 9751 to 9760 of 29210 articles

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...

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...

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...

Automatic segmentation of high-risk clinical target volume and organs at risk in brachytherapy of cervical cancer with a convolutional neural network.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
PURPOSE: This study aimed to design an autodelineation model based on convolutional neural networks for generating high-risk clinical target volumes and organs at risk in image-guided adaptive brachytherapy for cervical cancer.

Identification of medication-related fall risk in adults and older adults admitted to hospital: A machine learning approach.

Geriatric nursing (New York, N.Y.)
The study aimed to develop and validate, through machine learning, a fall risk prediction model related to prescribed medications specific to adults and older adults admitted to hospital. A case-control study was carried out in a tertiary hospital, i...

Epidemiological breast cancer prediction by country: A novel machine learning approach.

PloS one
Breast cancer remains a significant contributor to cancer-related deaths among women globally. We seek for this study to examine the correlation between the incidence rates of breast cancer and newly identified risk factors. Additionally, we aim to u...

Applying masked autoencoder-based self-supervised learning for high-capability vision transformers of electrocardiographies.

PloS one
The generalization of deep neural network algorithms to a broader population is an important challenge in the medical field. We aimed to apply self-supervised learning using masked autoencoders (MAEs) to improve the performance of the 12-lead electro...

Toward Interpretable Sleep Stage Classification Using Cross-Modal Transformers.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Accurate sleep stage classification is significant for sleep health assessment. In recent years, several machine-learning based sleep staging algorithms have been developed, and in particular, deep-learning based algorithms have achieved performance ...

Assessing the Effect of Cervical Transcutaneous Spinal Stimulation With an Upper Limb Robotic Exoskeleton and Surface Electromyography.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Transcutaneous spinal stimulation (TSS) is a promising rehabilitative intervention to restore motor function and coordination for individuals with spinal cord injury (SCI). The effects of TSS are most commonly assessed by evaluating muscle response t...

A Deep Learning-Derived Transdiagnostic Signature Indexing Hypoarousal and Impulse Control: Implications for Treatment Prediction in Psychiatric Disorders.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: Psychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. The Research Domain Criteria (RDoC) constitute a research classification system for psychiatric disorders based on dimensi...