AIMC Topic: Retrospective Studies

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Holographic 3D renal segments reconstruction protects renal function by promote choice of selective renal artery clamping during robot-assisted partial nephrectomy.

World journal of urology
OBJECTIVE: To investigate the impact of selective artery clamping (SAC) and main artery clamping (MAC) during robot-assisted partial nephrectomy (RAPN) on renal function and the influence of holographic three-dimensional (3D) reconstruction of renal ...

Differentiating Between Sexual Offending and Violent Non-sexual Offending in Men With Schizophrenia Spectrum Disorders Using Machine Learning.

Sexual abuse : a journal of research and treatment
Forensic psychiatric populations commonly contain a subset of persons with schizophrenia spectrum disorders (SSD) who have committed sex offenses. A comprehensive delineation of the features that distinguish persons with SSD who have committed sex of...

A deep learning pipeline for automated classification of vocal fold polyps in flexible laryngoscopy.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: To develop and validate a deep learning model for distinguishing healthy vocal folds (HVF) and vocal fold polyps (VFP) on laryngoscopy videos, while demonstrating the ability of a previously developed informative frame classifier in facilita...

75% radiation dose reduction using deep learning reconstruction on low-dose chest CT.

BMC medical imaging
OBJECTIVE: Few studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT using a quarter of the low do...

Identifying predictors of Day 5 blastocyst utilization rate using an artificial neural network.

Reproductive biomedicine online
RESEARCH QUESTION: Can artificial intelligence identify predictors of an increased Day 5 blastocyst utilization rate (D5BUR), which is one of the most informative key performance indicators in an IVF laboratory?

Development and validation of a deep learning-based fully automated algorithm for pre-TAVR CT assessment of the aortic valvular complex and detection of anatomical risk factors: a retrospective, multicentre study.

EBioMedicine
BACKGROUND: Pre-procedural computed tomography (CT) imaging assessment of the aortic valvular complex (AVC) is essential for the success of transcatheter aortic valve replacement (TAVR). However, pre-TAVR assessment is a time-intensive process, and t...

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data.

PloS one
With the advances in technology and data science, machine learning (ML) is being rapidly adopted by the health care sector. However, there is a lack of literature addressing the health conditions targeted by the ML prediction models within primary he...

Perioperative, renal function and oncological outcomes of robot-assisted radical nephroureterectomy for patients with upper tract urothelial carcinoma.

World journal of urology
PURPOSE: To report perioperative, renal function and oncological outcomes of robot-assisted radical nephroureterectomy (RNU) for patients with upper tract urothelial carcinoma (UTUC).

Dose reduction and toxicity of lenalidomide-dexamethasone in multiple myeloma: A machine-learning prediction model.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
PURPOSE: Lenalidomide remains an effective drug for multiple myeloma, but it is often associated with adverse events and requires dose adjustments. The objective of this study was to propose a model for predicting whether a patient would require dose...