AIMC Topic: Female

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Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.

Pediatric research
BACKGROUND: Early identification of children at risk of asthma can have significant clinical implications for effective intervention and treatment. This study aims to disentangle the relative timing and importance of early markers of asthma.

Artificial intelligence-adjudicated spatiotemporal dispersion: A patient-unique fingerprint of persistent atrial fibrillation.

Heart rhythm
BACKGROUND: Spatiotemporal dispersion-guided ablation is a tailored approach for patients in persistent atrial fibrillation (PsAF). The characterization of dispersion extent and distribution and its association with common clinical descriptors of PsA...

Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy. Timely diagnosis of ovarian cancer is difficult due to the lack of effective biomarkers. Laboratory tests are widely applied in clinical practice, and some have shown diagnostic ...

Illusory generalizability of clinical prediction models.

Science (New York, N.Y.)
It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically based on investigators observing a model's success in one or two d...

Prediction of Transfusion among In-patient Population using Temporal Pattern based Clinical Similarity Graphs.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Intelligent prediction of risk of blood transfusion among hospitalized patients can identify at-risk patients and provide timely information to the hospital to plan and reserve resources to meet the demand of blood transfusion. While previously propo...

Use of Health Belief Model-based Deep Learning to Understand Public Health Beliefs in Breast Cancer Screening from Social Media before and during the COVID-19 Pandemic.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Breast cancer is the second leading cause of cancer death for women in the United States. While breast cancer screening participation is the most effective method for early detection, screening rate has remained low. Given that understanding health p...

Transferable and Interpretable Treatment Effectiveness Prediction for Ovarian Cancer via Multimodal Deep Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Ovarian cancer, a potentially life-threatening disease, is often difficult to treat. There is a critical need for innovations that can assist in improved therapy selection. Although deep learning models are showing promising results, they are employe...

A novel artificial intelligence-assisted "vascular healing" diagnosis for prediction of future clinical relapse in patients with ulcerative colitis: a prospective cohort study (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Image-enhanced endoscopy has attracted attention as a method for detecting inflammation and predicting outcomes in patients with ulcerative colitis (UC); however, the procedure requires specialist endoscopists. Artificial intelli...

Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks.

Administration and policy in mental health
Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. ...

Registration of preoperative temporal bone CT-scan to otoendoscopic video for augmented-reality based on convolutional neural networks.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Patient-to-image registration is a preliminary step required in surgical navigation based on preoperative images. Human intervention and fiducial markers hamper this task as they are time-consuming and introduce potential errors. We aimed to...