AIMC Topic: Retrospective Studies

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External validation of SPARE nephrometery score in predicting overall complications, trifecta and pentafecta outcomes following robot-assisted partial nephrectomy.

Minerva urology and nephrology
BACKGROUND: There is an ongoing need and search for a simple yet accurate nephrometry scoring system for predicting the postoperative outcomes after partial nephrectomy (PN). Simplified PADUA Renal (SPARE) Nephrometry Scoring System, a simplified ver...

Development of a machine learning model for predicting pediatric mortality in the early stages of intensive care unit admission.

Scientific reports
The aim of this study was to develop a predictive model of pediatric mortality in the early stages of intensive care unit (ICU) admission using machine learning. Patients less than 18 years old who were admitted to ICUs at four tertiary referral hosp...

Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma.

Scientific reports
Survival analyses for malignancies, including renal cell carcinoma (RCC), have primarily been conducted using the Cox proportional hazards (CPH) model. We compared the random survival forest (RSF) and DeepSurv models with the CPH model to predict rec...

Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach.

Scientific reports
The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device's built-in softwa...

Retrospective analysis of the effect on interval cancer rate of adding an artificial intelligence algorithm to the reading process for two-dimensional full-field digital mammography.

Journal of medical screening
Interval cancers are a commonly seen problem in organized breast cancer screening programs and their rate is measured for quality assurance. Artificial intelligence algorithms have been proposed to improve mammography sensitivity, in which case it is...

Automatic Cephalometric Landmark Identification System Based on the Multi-Stage Convolutional Neural Networks with CBCT Combination Images.

Sensors (Basel, Switzerland)
This study was designed to develop and verify a fully automated cephalometry landmark identification system, based on multi-stage convolutional neural networks (CNNs) architecture, using a combination dataset. In this research, we trained and tested ...

A natural language processing approach for identifying temporal disease onset information from mental healthcare text.

Scientific reports
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variable is the date of psychosis symptom onset,...

LigaSure versus the standard technique (Hem-o-lok clips) for robot-assisted radical prostatectomy: a propensity score-matched study.

Journal of robotic surgery
The aim of the study is to compare the utility and efficacy of the LigaSure system and standard surgical clips for robot-assisted radical prostatectomy. The medical records of 473 patients who underwent robot-assisted radical prostatectomy between Ma...

A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

Cancer immunology research
A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are po...

Deep learning-based computer-aided diagnosis in screening breast ultrasound to reduce false-positive diagnoses.

Scientific reports
A major limitation of screening breast ultrasound (US) is a substantial number of false-positive biopsy. This study aimed to develop a deep learning-based computer-aided diagnosis (DL-CAD)-based diagnostic model to improve the differential diagnosis ...