AIMC Topic: Retrospective Studies

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Deep learning algorithms for predicting renal replacement therapy initiation in CKD patients: a retrospective cohort study.

BMC nephrology
BACKGROUND: Chronic kidney disease (CKD) requires accurate prediction of renal replacement therapy (RRT) initiation risk. This study developed deep learning algorithms (DLAs) to predict RRT risk in CKD patients by incorporating medical history and pr...

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

BMJ open
OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.

Prognostic factors among patients with pathological Grade Group 5 prostate cancer based on robot-associated radical prostatectomy specimens from a large Japanese cohort (MSUG94).

World journal of urology
PURPOSE: There are no definitive prognostic factors for patients with pathological Grade Group 5 (pGG 5) prostate cancer (PCa) undergoing robot-associated radical prostatectomy (RARP). This study aimed to explore the prognostic factors among patients...

Artificial intelligence of imaging and clinical neurological data for predictive, preventive and personalized (P3) medicine for Parkinson Disease: The NeuroArtP3 protocol for a multi-center research study.

PloS one
BACKGROUND: The burden of Parkinson Disease (PD) represents a key public health issue and it is essential to develop innovative and cost-effective approaches to promote sustainable diagnostic and therapeutic interventions. In this perspective the ado...

Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.

PloS one
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates (UAE) and Malaysia, emphasizing the importance of developing accurate and reliable forecasting mechanisms to guide public health responses and policies. In this study...

Automatic estimation of hallux valgus angle using deep neural network with axis-based annotation.

Skeletal radiology
OBJECTIVES: We developed the deep neural network (DNN) model to automatically measure hallux valgus angle (HVA) and intermetatarsal angle (IMA) on foot radiographs. The objective is to assess the accuracy of the model by comparing to the manual measu...

Quantitative measurement of the ureter on three-dimensional magnetic resonance urography images using deep learning.

Medical physics
BACKGROUND: Accurate measurement of ureteral diameters plays a pivotal role in diagnosing and monitoring urinary tract obstruction (UTO). While three-dimensional magnetic resonance urography (3D MRU) represents a significant advancement in imaging, t...

Comparative analysis of robotic single-site cholecystectomy outcomes between novice and expert surgeons.

Journal of robotic surgery
Single-incision laparoscopic cholecystectomy (SILC) has declined in popularity, posing a challenge for novice surgeons. However, robotic single-site cholecystectomy (RSSC) has gained popularity in hepatopancreatic surgery, suggesting a paradigm shift...

Robot-assisted single-port retroperitoneal partial nephrectomy with a novel purpose-built single-port robotic system with deformable surgical instruments.

World journal of urology
OBJECTIVE: To investigate the safety and feasibility of using a novel purpose-built single-port robotic system (the SHURUI Robotic Surgical System) with deformable surgical instruments to perform retroperitoneal single-port partial nephrectomy.

First prospective clinical assessment of the ILY robotic flexible ureteroscopy platform.

World journal of urology
PURPOSE: To present the initial prospective clinical assessment of the ILY robotic ureteroscopy manipulator platform, focusing on its safety and effectiveness.