AIMC Topic: Retrospective Studies

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Machine learning models for predicting tibial intramedullary nail length.

BMC musculoskeletal disorders
BACKGROUND: Tibial intramedullary nailing (IMN) represents a standard treatment for fractures of the tibial shaft. Nevertheless, accurately predicting the appropriate nail length prior to surgery remains a challenging endeavour. Conventional techniqu...

A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.

BMC infectious diseases
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely interven...

Use of ChatGPT for patient education involving HPV-associated oropharyngeal cancer.

American journal of otolaryngology
OBJECTIVE: This study aims to investigate the ability of ChatGPT to generate reliably accurate responses to patient-based queries specifically regarding oropharyngeal squamous cell carcinoma (OPSCC) of the head and neck.

Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a m...

X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head.

Scientific reports
This study aimed to develop an X-ray radiomics model for predicting collapse of early-stage osteonecrosis of the femoral head (ONFH). A total of 87 patients (111 hips; training set: n = 67, test set: n = 44) with non-traumatic ONFH at Association Res...

Machine learning-based return-to-work assessment system for acute myocardial infarction patients within 12 months.

Heart & lung : the journal of critical care
BACKGROUND: Returning to work is a critical indicator of recovery after acute myocardial infarction (AMI), and accurate identification of patients with low return-to-work rates is critical for timely intervention.

Interpretable machine learning model for prediction functional cure in chronic hepatitis B patients receiving Peg-IFN therapy: A multi-center study.

International journal of medical informatics
BACKGROUND: Functional cure is the ideal treatment goal for chronic hepatitis B (CHB) treatment. We developed and validated machine learning (ML) models to predict functional cure in CHB patients.

Performance of the artificial intelligence-based Swiss medical assessment system versus Manchester triage system in the emergency department: A retrospective analysis.

The American journal of emergency medicine
BACKGROUND: The emergence of artificial intelligence (AI) offers new opportunities for applications in emergency medicine, including patient triage. This study evaluates the performance of the Swiss Medical Assessment System (SMASS), an AI-based deci...

Dose-response association between OGTT and adverse perinatal outcomes after IVF treatment: A cohort study based on a twin population.

Journal of endocrinological investigation
BACKGROUND: Investigate the association between Oral Glucose Tolerance Test (OGTT) after in vitro fertilization (IVF) treatment and adverse maternal and neonatal outcomes in twin pregnancies.