AIMC Topic: Retrospective Studies

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Orthopedic perioperative nursing under navigation nurse management: Machine learning-based risk prediction models for postoperative recovery quality and explainable artificial intelligence analysis.

Medicine
This study aimed to evaluate the effectiveness of navigation nurse management (NNM) in orthopedic perioperative care and develop machine learning (ML) models to predict postoperative recovery quality. We sought to identify key factors influencing rec...

Machine learning-based screening of characteristic factors for urinary tract infection following ureteral stone surgery and construction and validation of risk prediction models.

Medicine
Ureteroscopic lithotripsy has emerged as the cornerstone treatment modality for ureteral stones due to its exceptional success rates and minimal complication profiles. Nevertheless, postoperative urinary tract infection (UTI) remains a prevalent and ...

Leveraging Hematologic Single-Cell Measurements for Patient Triage and Outcome Prediction.

The journal of applied laboratory medicine
BACKGROUND: The complete blood count (CBC) is widely used across nearly all areas of medicine. While standard CBC markers reflect basic summaries of the blood cells, modern hematology analyzers generate many additional markers from the underlying dat...

Utilization of a Digital Automated Cell Morphology Analyzer Results for Determining Differential White Blood Cell Counts in a Turkish Pediatric Population.

The journal of applied laboratory medicine
BACKGROUND: Manual morphological analysis of peripheral blood smears (PBS) with light microscopy is an essential diagnostic and monitoring tool. Recently, automated morphology analyzers have been developed that can preclassify cells using artificial ...

Deep Learning Reconstruction for 7T MP2RAGE and SPACE MRI: Improving Image Quality at High Acceleration Factors.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction has been successful in realizing otherwise impracticable acceleration factors and improving image quality in conventional MRI field strengths; however, there has been limited application to ul...

Multimodal Language Model for Jaw Osteonecrosis Diagnosis and Treatment.

Journal of dental research
Owing to the complexity of the clinical manifestations in patients with osteonecrosis of the jaw (ONJ), particularly in settings lacking oral and maxillofacial surgery, timely and accurate treatment remains challenging. Here, we developed an integrat...

Machine learning using serial changes in proteinuria during initial steroid therapy to predict treatment response and immunosuppressant use in pediatric idiopathic nephrotic syndrome.

Clinical and experimental nephrology
BACKGROUND: Epidemiological studies on idiopathic nephrotic syndrome (INS) in children have identified no definitive factors predicting steroid-resistant nephrotic syndrome (SRNS) or frequent relapsing nephrotic syndrome. Research using machine learn...

Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A Retrospective Registry-Based Study.

Annals of emergency medicine
STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insights into the out-of-hospital pathways of patients with stroke. This study explored the ability of EMCC...

Personalized survival benefit estimation from living donor liver transplantation with a novel machine learning method for confounding adjustment.

Journal of hepatology
BACKGROUND & AIMS: Addressing many clinical questions, such as estimating survival differences between living donor (LDLT) and deceased donor liver transplantation (DDLT), relies on observational studies, as randomized-controlled trials (RCTs) are of...

Optimizing MRI sequence classification performance: insights from domain shift analysis.

European radiology
BACKGROUND: MRI sequence classification becomes challenging in multicenter studies due to variability in imaging protocols, leading to unreliable metadata and requiring labor-intensive manual annotation. While numerous automated MRI sequence identifi...