AIMC Topic: Female

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Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

Clinical interventions in aging
BACKGROUND: Hip fractures have become a significant health concern, particularly among super-aged patients, who were at a high risk of postoperative pneumonia due to their frailty and the presence of multiple comorbidities. This study aims to establi...

Introduction to Spine Injuries in the Pickleball Athlete.

The Journal of the American Academy of Orthopaedic Surgeons
INTRODUCTION: Pickleball is one of the fastest growing sports in the United States. Despite its popularity, there is limited research on pickleball-related orthopaedic injuries, particularly in the spine. This study aims to provide a deeper understan...

Prospective External Validation of an AI-Based Emergency Department Pneumonia Disposition Prediction Tool.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
This shadow deployment evaluated an externally-developed AI tool to predict disposition using chest X-rays (CXR) in patients with community-acquired pneumonia (CAP) in the Emergency Department (ED). Retrospective and prospective external validations...

A deep learning-based psi CT network effectively predicts early recurrence after hepatectomy in HCC patients.

Abdominal radiology (New York)
BACKGROUND: Hepatocellular carcinoma (HCC) exhibits a high recurrence rate, and early recurrence significantly jeopardizes patient prognosis, necessitating reliable methods for early recurrence prediction.

Accuracy of 7 artificial intelligence-based intraocular lens power calculation formulas in medium-long eyes: 2-center study.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To compare accuracy of 7 artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in medium-long eyes DESIGN: Retrospective observational study.

Multi-parametric MRI Habitat Radiomics Based on Interpretable Machine Learning for Preoperative Assessment of Microsatellite Instability in Rectal Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: This study constructed an interpretable machine learning model based on multi-parameter MRI sub-region habitat radiomics and clinicopathological features, aiming to preoperatively evaluate the microsatellite instability (MSI...

Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning.

Transplant immunology
BACKGROUND: Allogeneic hematopoietic stem transplantation (allo-HSCT) constitutes a curative treatment for various hematological malignancies. However, various complications limit the therapeutic efficacy of this approach, increasing the morbidity an...

Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer.

Oncogene
CDK4/6 inhibitors in combination with endocrine therapy are widely used to treat HR+/HER2- metastatic breast cancer leading to improved progression-free survival (PFS) compared to single agent endocrine therapy. Over 300 patients receiving standard-o...

Deep learning-based LDL-C level prediction and explainable AI interpretation.

Computers in biology and medicine
This study investigates the use of deep learning (DL) models to predict low-density lipoprotein cholesterol (LDL-C) levels. The dataset obtained from New York-Presbyterian Hospital/Weill Cornell Medical Center includes triglycerides (TG), total chole...