AIMC Topic: Retrospective Studies

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Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.

AMIA ... Annual Symposium proceedings. AMIA Symposium
While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) models in a retrospective cohort study with a large sample size. We analyzed the association between depr...

[CLINICAL EVALUATION OF THERAPEUTIC EFFECT PREDICTORS IN PEMBROLIZUMAB FOR ADVANCED UROTHELIAL CANCER].

Nihon Hinyokika Gakkai zasshi. The japanese journal of urology
(Purpose) We performed a clinical retrospective study on the evaluation of pembrolizumab treatment results for advanced urothelial cancer in our hospital. (Materials and Methods) Twenty-seven patients diagnosed with advanced or metastatic urothelial ...

Efficacy of Intraoperative Cell Salvage on Perioperative Blood Transfusion in Pelvic and Acetabular Surgery: A Matched Cohort Analysis.

The Iowa orthopaedic journal
BACKGROUND: Pelvic fractures often result in traumatic and intraoperative blood loss. Cell salvage (CS) is a tool where autologous blood lost during surgery is collected and recycled with anticoagulation, centrifugation to separate red blood cells, a...

Transurethral Cylindrical Water Sac Prostate Enlargement Surgery for the Treatment of Small-Volume Benign Prostatic Hyperplasia: A Retrospective Analysis.

Annali italiani di chirurgia
AIM: To investigate the clinical efficacy of transurethral columnar balloon dilation of prostate (TUCBDP) in the treatment of small-volume benign prostatic hyperplasia (BPH) and provide the optimal treatment for the surgical treatment of small volume...

Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier.

Technology in cancer research & treatment
INTRODUCTION: This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patien...

Prediction of T Stage of Rectal Cancer After Neoadjuvant Therapy by Multi-Parameter Magnetic Resonance Radiomics Based on Machine Learning Algorithms.

Technology in cancer research & treatment
INTRODUCTION: Since the response of patients with rectal cancer (RC) to neoadjuvant therapy is highly variable, there is an urgent need to develop accurate methods to predict the post-treatment T (pT) stage. The purpose of this study was to evaluate ...

Interpretable Machine Learning Approach for Predicting 30-Day Mortality of Critical Ill Patients with Pulmonary Embolism and Heart Failure: A Retrospective Study.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
BACKGROUND: Pulmonary embolism (PE) patients combined with heart failure (HF) have been reported to have a high short-term mortality. However, few studies have developed predictive tools of 30-day mortality for these patients in intensive care unit (...

Prediction of Vancomycin-Associated Nephrotoxicity Based on the Area under the Concentration-Time Curve of Vancomycin: A Machine Learning Analysis.

Biological & pharmaceutical bulletin
Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxicity; however, they have notable limitations. Specifically, they do not use the area under the concentration-time curve (AUC) as recommended in the la...

Machine Learning-Based Prediction of Pulmonary Embolism Prognosis Using Nutritional and Inflammatory Indices.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
PURPOSE: This study aimed to create and assess machine learning (ML) models that utilize nutritional and inflammatory indices, focusing on the advanced lung cancer inflammation index (ALI) and neutrophil-to-albumin ratio (NAR), to improve the predict...

Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.

Technology in cancer research & treatment
This study aimed to develop an automated classification framework for distinguishing between cervical cancer tumor and normal uterine tissue, leveraging CT images for radiomics feature extraction. We retrospectively analyzed CT images from 117 cervic...