AIMC Topic: Female

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A comprehensive deep learning approach to improve enchondroma detection on X-ray images.

Scientific reports
An enchondroma is a benign neoplasm of mature hyaline cartilage that proliferates from the medullary cavity toward the cortical bone. This results in the formation of a significant endogenous mass within the medullary cavity. Although enchondromas ar...

The effects of multi-sensory public seating on emotion regulation in youth communities.

Scientific reports
As urban housing pressures intensify, co-living communities are emerging as a new residential model for young adults. However, the high prevalence of depression and anxiety among this population highlights the potential value of incorporating emotion...

Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study.

Scientific reports
Cerebral-cardiac syndrome (CCS) is a severe cardiac complication following acute ischemic stroke, often associated with adverse outcomes. This study developed and validated a machine learning (ML) model to predict CCS using clinical, laboratory, and ...

Deep learning approach for screening neonatal cerebral lesions on ultrasound in China.

Nature communications
Timely and accurate diagnosis of severe neonatal cerebral lesions is critical for preventing long-term neurological damage and addressing life-threatening conditions. Cranial ultrasound is the primary screening tool, but the process is time-consuming...

Evaluating the Prototype of a Clinical Decision Support System in Primary Care: Qualitative Study.

JMIR formative research
BACKGROUND: General practitioners are confronted with a wide variety of diseases and sometimes diagnostic uncertainty. Clinical decision support systems could be valuable to improve diagnosis, but existing tools are not adapted to the requirements an...

Exploring the Characteristics of Online Counseling Chat Services for Youth in Europe: Web Search Study.

JMIR mental health
BACKGROUND: Online counseling chat services are increasingly used by young people worldwide. A growing body of literature supports the use and effectiveness of these services for adolescent mental health. However, there is also a need to provide an o...

The prediction models for the optimal timing of surgical intervention for necrotizing enterocolitis: nomogram vs. five machine learning models.

Pediatric surgery international
BACKGROUND: Necrotizing enterocolitis (NEC) is one of the most common diseases that pose serious threats to the life of newborns. In clinical practice, NEC is typically treated by surgical intervention, but it is still difficult to identify the timin...

Multimodal analysis of cell-free DNA enhances differentiation of early-stage breast cancer from benign lesions and healthy individuals.

BMC biology
BACKGROUND: Breast cancer (BC) remains the second leading cause of cancer-related mortality among women worldwide. Liquid biopsy based on circulating tumor DNA (ctDNA) offers a promising noninvasive approach for early detection; however, differentiat...

Predicting post-liver transplantation mortality: a retrospective cohort study on risk factor identification and prognostic nomogram construction.

European journal of medical research
BACKGROUND: To identify risk factors for post-transplant mortality and develop a machine learning-integrated prognostic tool to optimise clinical decision-making in liver transplantation (LT) recipients.

Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.

Alzheimer's research & therapy
BACKGROUND AND OBJECTIVES: Early and cost-effective identification of amyloid positivity is crucial for Alzheimer's disease (AD) diagnosis. While amyloid PET is the gold standard, plasma biomarkers such as phosphorylated tau 217 (pTau217) provide a p...