AIMC Topic: Retrospective Studies

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Deep Learning-Facilitated Study of the Rate of Change in Photoreceptor Outer Segment Metrics in RPGR-Related X-Linked Retinitis Pigmentosa.

Investigative ophthalmology & visual science
PURPOSE: The aim of this retrospective cohort study was to obtain three-dimensional (3D) photoreceptor outer segment (OS) metrics measurements with the assistance of a deep learning model (DLM) and to evaluate the longitudinal change in OS metrics an...

Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Radiology
Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-intensive reading tasks. Purpose To investigate if deep learning (DL) algorithms can be used to triage ma...

Pilot study of machine learning in the task of distinguishing high and low-grade pediatric hydronephrosis on ultrasound.

Investigative and clinical urology
PURPOSE: Hydronephrosis is a common pediatric urological condition, characterized by dilation of the renal collecting system. Accurate identification of the severity of hydronephrosis is crucial in clinical management, as high-grade hydronephrosis ca...

Robot-assisted thoracoscopic surgery for mediastinal tumours in children: a single-centre retrospective study of 149 patients.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The purpose of this retrospective study was to summarize our experience in performing robot-assisted thoracoscopic surgery (RATS) for mediastinal tumours in children to investigate its safety and feasibility.

Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Histopathological examination is a crucial step in the diagnosis and treatment of many major diseases. Aiming to facilitate diagnostic decision making and improve the workload of pathologists, we developed an artificial intelligence (AI)-...

A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography.

JAMA ophthalmology
IMPORTANCE: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully autom...

Robot-Assisted Repair of Ureteroenteric Strictures After Cystectomy with Urinary Diversion: Technique Description and Outcomes from the European Robotic Urology Section Scientific Working Group.

Journal of endourology
Robot-assisted repair of benign ureteroenteric anastomotic strictures (UAS) provides an alternative to the open approach. We aimed to report short-, medium-, and long-term outcomes for robotic repair of benign UAS, and to provide a detailed video de...

Improving Cardiology-Rehospitalization Prediction Through the Synergy of Process Mining and Deep Learning: An Innovative Approach.

Studies in health technology and informatics
Nowadays, hospitals are facing the need for an accurate prediction of rehospitalizations. Rehospitalizations, indeed, represent both a high financial burden for the hospital and a proxy measure of care quality. The current work aims to address such a...

A novel robot-assisted knee arthroplasty system (ROSA) and 1-year outcome: A single center experience.

Medicine
BACKGROUND: Total knee arthroplasty is a successful procedure in the treatment of knee osteoarthritis. Searches in surgical technique have focused surgeons in particular on implant alignment. For this purpose, the use of robot-assisted total knee art...

The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review.

International journal for quality in health care : journal of the International Society for Quality in Health Care
Falls are a common problem associated with significant morbidity, mortality, and economic costs. Current fall prevention policies in local healthcare settings are often guided by information provided by fall risk assessment tools, incident reporting,...