AIMC Topic: Retrospective Studies

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Machine Learning Model to Guide Empirical Antimicrobial Therapy in Febrile Neutropenic Patients With Hematologic Malignancies.

Anticancer research
BACKGROUND/AIM: Optimal antimicrobial selection for patients with febrile neutropenia (FN) may differ depending on the underlying mechanisms. We aimed to develop a model for predicting the severity of bacteremia in patients with FN and hematologic ma...

Artificial intelligence assisted nutritional risk evaluation model for critically ill patients: Integration of explainable machine learning in intensive care nutrition.

Asia Pacific journal of clinical nutrition
BACKGROUND AND OBJECTIVES: Critically ill patients require individualized nutrition support, with assessment tools like Nutrition Risk Screening 2002 and Nutrition Risk in the Critically Ill scores. Challenges in continu-ous nutrition care prompt the...

Diagnostic Stewardship of Blood Cultures in the Pediatric ICU Using Machine Learning.

Hospital pediatrics
OBJECTIVE: The medical community recently experienced a severe shortage of blood culture media bottles. Rates of blood stream infection (BSI) among critically ill children are low. We sought to design a machine learning (ML) model able to identify ch...

Stratifying Risk for Postpartum Depression at Time of Hospital Discharge.

The American journal of psychiatry
OBJECTIVE: Postpartum depression (PPD) is a major contributor to postpartum morbidity and mortality. Beyond efforts at routine screening, risk stratification models could enable more targeted interventions in settings with limited resources. The auth...

Predicting response to anti-VEGF therapy in neovascular age-related macular degeneration using random forest and SHAP algorithms.

Photodiagnosis and photodynamic therapy
PURPOSE: This study aimed to establish and validate a prediction model based on machine learning methods and SHAP algorithm to predict response to anti-vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration ...

Prediction of endoscopic restenosis after endoscopic balloon dilation in patients with Crohn's disease: a machine learning approach.

Surgical endoscopy
BACKGROUND: Endoscopic balloon dilation (EBD) is recognized as a minimally invasive and effective procedure for managing intestinal stenosis in patients with Crohn's disease (CD). It offers an alternative to surgery and has been shown to improve the ...

Fully automated image quality assessment based on deep learning for carotid computed tomography angiography: A multicenter study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To develop and evaluate the performance of fully automated model based on deep learning and multiple logistics regression algorithm for image quality assessment (IQA) of carotid computed tomography angiography (CTA) images.

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

Diabetes research and clinical practice
AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day and 90-day mortality in septic ICU patients.

MRI-based multimodal AI model enables prediction of recurrence risk and adjuvant therapy in breast cancer.

Pharmacological research
Timely intervention and improved prognosis for breast cancer patients rely on early metastasis risk detection and accurate treatment predictions. This study introduces an advanced multimodal MRI and AI-driven 3D deep learning model, termed the 3D-MMR...

Development and Validation of an Explainable Machine Learning Model for Warning of Hepatitis E Virus-Related Acute Liver Failure.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Early identification of patients with acute hepatitis E (AHE) who are at high risk of progressing to hepatitis E virus-related acute liver failure (HEV-ALF) is crucial for enabling timely monitoring and intervention. This multice...