AIMC Topic: Female

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Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.

Academic radiology
RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur attenuation values and radiomics features at routine CT to predict hip fragility fracture using machine learning methods.

Prenatal Diagnostics Using Deep Learning: A Dual Approach to Plane Localization and Cerebellum Segmentation in Ultrasound Images.

Journal of clinical ultrasound : JCU
OBJECTIVE: The fetal ultrasound examination is the significant task of mid-term pregnancy inspection and the accurate localization as well as the segmentation of the cerebellum is crucial for clinical diagnosis. This research focuses on developing de...

Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study.

The Lancet. Digital health
BACKGROUND: Emerging evidence suggests that artificial intelligence (AI) can increase cancer detection in mammography screening while reducing screen-reading workload, but further understanding of the clinical impact is needed.

Exploring the impact of AI-enhanced virtual tourism on Tourists' pro-environmental behavior: A stimulus-organism-response model perspective.

Acta psychologica
This study explores the potential of AI-enhanced virtual tourism to promote pro-environmental behavior (PEB) in cultural heritage tourism in China. Employing the stimulus-organism-response (SOR) model, we examine how five stimuli-accessibility, authe...

An AI-assisted morphoproteomic approach is a supportive tool in esophagitis-related precision medicine.

EMBO molecular medicine
Esophagitis is a frequent, but at the molecular level poorly characterized condition with diverse underlying etiologies and treatments. Correct diagnosis can be challenging due to partially overlapping histological features. By proteomic profiling of...

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

Journal of the American Heart Association
BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion and screening tools not being easily accessible such as echocardiography. A new readily available scre...

Clinician Experiences With Ambient Scribe Technology to Assist With Documentation Burden and Efficiency.

JAMA network open
IMPORTANCE: Timely evaluation of ambient scribing technology is warranted to assess whether this technology can lessen the burden of clinical documentation on clinicians.

Interoperable Models for Identifying Critically Ill Children at Risk of Neurologic Morbidity.

JAMA network open
IMPORTANCE: Decreasing mortality in the field of pediatric critical care medicine has shifted practicing clinicians' attention to preserving patients' neurodevelopmental potential as a main objective. Earlier identification of critically ill children...

Machine learning analysis of the relationships between traumatic childbirth experience with positive and negative fertility motivations in Iran in a community-based sample.

Reproductive health
BACKGROUND: Psychologically traumatic childbirth leads to short and long-term negative impacts on a woman's health and impacts future reproductive decisions. Considering the importance of fertility growth and strengthening positive fertility motivati...

Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.

BMC medical informatics and decision making
BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and intervention in risk populations...