AIMC Topic: Retrospective Studies

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Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study.

BMC infectious diseases
BACKGROUND: Pertussis is a highly contagious respiratory disease. Even though vaccination has reduced the incidence, cases have resurfaced in certain regions due to immune escape and waning vaccine efficacy. Identifying high-risk patients to mitigate...

Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches.

BMC endocrine disorders
BACKGROUND: Hyperglycemic crisis is one of the most common and severe complications of diabetes mellitus, associated with a high motarlity rate. Emergency admissions due to hyperglycemic crisis remain prevalent and challenging. This study aimed to de...

Thigh muscle index as a valuable prognostic marker in middle-aged male patients undergoing liver transplantation.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
In liver transplantation (LT), determining the optimal recipients is crucial, and the MELD score has been used for this purpose. However, the MELD score does not reflect functional status, leading to the evaluation of sarcopenia. While the L3 skeleta...

Using deep learning to enhance reporting efficiency and accuracy in degenerative cervical spine MRI.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Cervical spine MRI is essential for evaluating degenerative cervical spondylosis (DCS) but is time-consuming to report and subject to interobserver variability. The integration of artificial intelligence in medical imaging offers ...

Retrospective evaluation of a CE-marked AI system, including 1,017,208 mammography screening examinations.

European radiology
OBJECTIVES: To retrospectively evaluate the performance of a CE-marked AI system for identifying breast cancer on screening mammograms. Evidence from large retrospective studies is crucial for planning prospective studies and to further ensure safe i...

Cesarean Scar Pregnancy Prognostic Classification System Based on Machine-Learning and Traditional Linear Scoring Models.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Cesarean scar pregnancy (CSP) refers to a special type of pregnancy with a variable prognosis. We aimed to establish a prognostic classification system using ultrasound and clinical features to provide a reference for management strategie...

A Novel Visual Model for Predicting Prognosis of Resected Hepatoblastoma: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to evaluate the application of a contrast-enhanced CT-based visual model in predicting postoperative prognosis in patients with hepatoblastoma (HB).

Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score.

Critical care explorations
BACKGROUND: Early detection of clinical deterioration using machine-learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not t...