AIMC Topic: Retrospective Studies

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Assessing the Utility of a Machine-Learning Model to Assist With the Assignment of the American Society of Anesthesiology Physical Status Classification in Pediatric Patients.

Anesthesia and analgesia
BACKGROUND: The American Society of Anesthesiologists Physical Status Classification System (ASA-PS) is used to classify patients' health before delivering an anesthetic. Assigning an ASA-PS Classification score to pediatric patients can be challengi...

Fully automated assessment of the knee alignment on long leg radiographs following corrective knee osteotomies in patients with valgus or varus deformities.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The assessment of the knee alignment on long leg radiographs (LLR) postoperative to corrective knee osteotomies (CKOs) is highly dependent on the reader's expertise. Artificial Intelligence (AI) algorithms may help automate and standard...

Deep learning in voice analysis for diagnosing vocal cord pathologies: a systematic review.

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
OBJECTIVES: With smartphones and wearable devices becoming ubiquitous, they offer an opportunity for large-scale voice sampling. This systematic review explores the application of deep learning models for the automated analysis of voice samples to de...

Deep learning prediction of hospital readmissions for asthma and COPD.

Respiratory research
QUESTION: Severe asthma and COPD exacerbations requiring hospitalization are linked to increased disease morbidity and healthcare costs. We sought to identify Electronic Health Record (EHR) features of severe asthma and COPD exacerbations and evaluat...

Value of CT quantification in progressive fibrosing interstitial lung disease: a deep learning approach.

European radiology
OBJECTIVES: To evaluate the relationship of changes in the deep learning-based CT quantification of interstitial lung disease (ILD) with changes in forced vital capacity (FVC) and visual assessments of ILD progression, and to investigate their progno...

Development and Validation of a Deep-Learning Model to Predict Total Hip Replacement on Radiographs: The Total Hip Replacement Prediction (THREP) Model.

The Journal of bone and joint surgery. American volume
BACKGROUND: There are few methods for accurately assessing the risk of total hip arthroplasty (THA) in patients with osteoarthritis. A novel and reliable method that could play a substantial role in research and clinical routine should be investigate...

Correcting synthetic MRI contrast-weighted images using deep learning.

Magnetic resonance imaging
Synthetic magnetic resonance imaging (MRI) offers a scanning paradigm where a fast multi-contrast sequence can be used to estimate underlying quantitative tissue parameter maps, which are then used to synthesize any desirable clinical contrast by ret...

Comparison of Bone-setting Robots and Conventional Reduction in the Treatment of Intertrochanteric Fracture: A Retrospective Study.

Orthopaedic surgery
OBJECTIVE: Intertrochanteric fracture of the femur is a common fracture in older people. Due to the poor systemic condition and prognosis of elderly patients, it is prone to more complications. We introduce the bone-setting concept in the design of t...