AIMC Topic: Retrospective Studies

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Robot Navigation System Assisted PFNA Fixation of Femoral Intertrochanteric Fractures in the Elderly: A Retrospective Clinical Study.

Clinical interventions in aging
OBJECTIVE: The incidence of hip fracture in the elderly is increasing. Robot navigation technology has the advantages of minimally invasive and accurate. To explore the difference between the clinical effects of proximal femoral anti-rotation intrame...

Using machine learning to assess the extent of busy ambulances and its impact on ambulance response times: A retrospective observational study.

PloS one
BACKGROUND: Ambulance response times are considered important. Busy ambulances are common, but little is known about their effect on response times.

Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study.

Frontiers in public health
OBJECTIVE: The study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources.

Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning.

The Laryngoscope
OBJECTIVE: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos.

Robot-Assisted Pelvic Dissection for Enlarged Lymph Nodes in Melanoma Improves Recovery with Equivalent Oncological Outcomes to Open Pelvic Dissection.

Annals of surgical oncology
BACKGROUND: Robot-assisted pelvic lymph node dissection (rPLND) has been reported in heterogenous groups of patients with melanoma, including macroscopic or at-high-risk-for microscopic metastasis. With changing indications for surgery in melanoma, a...

Utilizing Artificial Intelligence-Based Deformable Registration for Global and Layer-Specific Cardiac MRI Strain Analysis in Healthy Children and Young Adults.

Academic radiology
RATIONALE AND OBJECTIVES: The absence of published reference values for multilayer-specific strain measurement using cardiac magnetic resonance (CMR) in young healthy individuals limits its use. This study aimed to establish normal global and layer-s...

A deep learning model based on MRI for prediction of vessels encapsulating tumour clusters and prognosis in hepatocellular carcinoma.

Abdominal radiology (New York)
PURPOSE: This study aimed to build and evaluate a deep learning (DL) model to predict vessels encapsulating tumor clusters (VETC) and prognosis preoperatively in patients with hepatocellular carcinoma (HCC).

Identification of high-risk population of pneumoconiosis using deep learning segmentation of lung 3D images and radiomics texture analysis.

Computer methods and programs in biomedicine
OBJECTION: The aim of this study is to develop an early-warning model for identifying high-risk populations of pneumoconiosis by combining lung 3D images and radiomics lung texture features.

A computed tomography urography-based machine learning model for predicting preoperative pathological grade of upper urinary tract urothelial carcinoma.

Cancer medicine
OBJECTIVES: Development and validation of a computed tomography urography (CTU)-based machine learning (ML) model for prediction of preoperative pathology grade of upper urinary tract urothelial carcinoma (UTUC).

Evaluating the Reliability of a Remote Acuity Prediction Tool in a Canadian Academic Emergency Department.

Annals of emergency medicine
STUDY OBJECTIVE: There is increasing interest in harnessing artificial intelligence to virtually triage patients seeking care. The objective was to examine the reliability of a virtual machine learning algorithm to remotely predict acuity scores for ...