AIMC Topic: Adult

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Preoperative CT imaging and machine learning models for predicting ureteral access sheath placement success in non-stented patients with ureteral calculi: a retrospective cohort study.

World journal of urology
OBJECTIVE: This study aims to both develop and evaluate a predictive model for ureteral access sheath(UAS)placement success using preoperative CT-based 3D ureteral imaging and machine learning techniques. Specifically, it investigates the impact of u...

Predicting human decision-making across task conditions via individuality transfer.

eLife
Predicting an individual's behavior in one task condition based on their behavior in a different condition is a key challenge in modeling individual decision-making tendencies. We propose a novel framework that addresses this challenge by leveraging ...

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...

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...

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...

Identification and validation of PANX1 as an inflammasome-related biomarker in gestational diabetes mellitus: insights from machine learning and experimental approaches.

Mammalian genome : official journal of the International Mammalian Genome Society
Gestational diabetes mellitus (GDM) is characterized by glucose intolerance during pregnancy, resulting from insulin resistance, and is associated with increased maternal and neonatal risks. Inflammasomes play a critical role in GDM pathophysiology b...

Stratification of viral shedding patterns in saliva of COVID-19 patients.

eLife
Living with COVID-19 requires continued vigilance against the spread and emergence of variants of concern (VOCs). Rapid and accurate saliva diagnostic testing, alongside basic public health responses, is a viable option contributing to effective tran...