AIMC Topic: Female

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Construction of a diagnostic model for tuberculosis based on long non-coding RNA.

Annals of medicine
BACKGROUND: The World Health Organization encourages the development of novel diagnostic tools based on 'non-sputum' samples to meet global goals for tuberculosis (TB) control. We aimed to develop a machine learning-driven model for TB diagnosis, usi...

Predicting the progression of difficult-to-treat rheumatoid arthritis by a machine learning scoring system, from the FIRST registry.

RMD open
OBJECTIVES: This study aimed to develop and validate a prediction model for the future progression of difficult-to-treat rheumatoid arthritis (D2T RA) and support the precise use of biologic and targeted synthetic disease-modifying antirheumatic drug...

Deep learning algorithm for semiquantification of spinal inflammation in axial spondyloarthritis.

RMD open
OBJECTIVE: To develop a deep learning algorithm for semiquantification of spinal inflammation in patients with axial spondyloarthritis (SpA). METHODS: The study included 330 participants with axial SpA. All patients underwent whole spine MRI with sho...

NLP-ROPCare: predicting retinopathy of prematurity with admission notes using natural language processing.

BMJ open ophthalmology
OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of blindness in children worldwide, requiring more efficient models to help predict treatment-requiring ROP. Our study aimed to develop a new prediction model for ROP occurrence and seve...

Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BMJ mental health
BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJECTIVE: To develop and externally validate 5-year CVD risk prediction models for people with schizophr...

Barriers and facilitators to implementing the living guideline development framework in oncology: a mixed methods study.

BMJ open
OBJECTIVE: To explore stakeholder experiences with implementing the living guideline (LG) development framework in oncology, and to identify barriers, facilitators and solutions to support its uptake and sustainability. DESIGN: An exploratory sequent...

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study.

JMIR medical informatics
BACKGROUND: There is a lack of venous thromboembolism (VTE) risk prediction models based on gene expression information. OBJECTIVE: This study aimed to construct a VTE prediction model based on whole blood gene expression profiling, by performing a c...

Insights Into Factors Affecting Nurses' Knowledge of and Attitudes Toward AI and Implications for Successful AI Integration in Critical Care: Cross-Sectional Study.

JMIR nursing
BACKGROUND: Assessing the current landscape of nurses' knowledge and attitudes is a critical first step in facilitating a smooth and effective transition toward artificial intelligence (AI)-enhanced critical care. OBJECTIVE: This study aimed to asses...

External validation of the IHXGboost-P model to predict incisional hernia after midline laparotomy.

Hernia : the journal of hernias and abdominal wall surgery
BACKGROUND: Incisional hernia (IH) is a significant complication that occurs after midline laparotomy and is associated with high morbidity and economic impacts. A fundamental goal of preventing IH is to determine which patients are considered low- o...