AIMC Topic: Retrospective Studies

Clear Filters Showing 6271 to 6280 of 9989 articles

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

PloS one
BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased morbidity, mortality and costs. Healthcare associated urinary tract infections (HA-UTI) accounts fo...

Subfoveal choroidal thickness changes after intravitreal ranibizumab injections in different patterns of diabetic macular edema using a deep learning-based auto-segmentation.

International ophthalmology
PURPOSE: To evaluate the effect of intravitreal injection of ranibizumab (IVR) on subfoveal choroidal thickness (SFCT) and its relationship with central macular thickness (CMT) and best-corrected visual acuity (BCVA) changes in eyes with center-invol...

Deep Learning-based Angiogram Generation Model for Cerebral Angiography without Misregistration Artifacts.

Radiology
Background Digital subtraction angiography (DSA) generates an image by subtracting a mask image from a dynamic angiogram. However, patient movement-caused misregistration artifacts can result in unclear DSA images that interrupt procedures. Purpose T...

Development and Validation of a Radiomics Model for Differentiating Bone Islands and Osteoblastic Bone Metastases at Abdominal CT.

Radiology
Background It is important to diagnose sclerotic bone lesions in order to determine treatment strategy. Purpose To evaluate the diagnostic performance of a CT radiomics-based machine learning model for differentiating bone islands and osteoblastic bo...

Exploring the predictive value of additional peritumoral regions based on deep learning and radiomics: A multicenter study.

Medical physics
PURPOSE: The present study assessed the predictive value of peritumoral regions on three tumor tasks, and further explored the influence of peritumors with different sizes.

Deep learning and ensemble stacking technique for differentiating polypoidal choroidal vasculopathy from neovascular age-related macular degeneration.

Scientific reports
Polypoidal choroidal vasculopathy (PCV) and neovascular age-related macular degeneration (nAMD) share some similarity in clinical imaging manifestations. However, their disease entity and treatment strategy as well as visual outcomes are very differe...

[Robot-assisted Living Donor Nephrectomy - Technical Aspects and Initial Evidence].

Zentralblatt fur Chirurgie
Minimally invasive donor nephrectomy has become the standard procedure in most transplant centres over the past two decades and has contributed to a reduction in postoperative morbidity for the donor. Robot-assisted technology is an alternative to co...

Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study.

BMC medicine
BACKGROUND: Targeted therapy and immunotherapy put forward higher demands for accurate lung cancer classification, as well as benign versus malignant disease discrimination. Digital whole slide images (WSIs) witnessed the transition from traditional ...

Predicting postoperative opioid use with machine learning and insurance claims in opioid-naïve patients.

American journal of surgery
BACKGROUND: The clinical impact of postoperative opioid use requires accurate prediction strategies to identify at-risk patients. We utilize preoperative claims data to predict postoperative opioid refill and new persistent use in opioid-naïve patien...

Supervised machine learning-based prediction for in-hospital pressure injury development using electronic health records: A retrospective observational cohort study in a university hospital in Japan.

International journal of nursing studies
BACKGROUND: In hospitals, nurses are responsible for pressure injury risk assessment using several kinds of risk assessment scales. However, their predictive validity is insufficient to initiate targeted preventive strategy for each patient. The use ...