AIMC Topic: Middle Aged
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Development and application of an intelligent pressure injury assessment system using AI image recognition.
Technology and health care : official journal of the European Society for Engineering and Medicine
Dec 9, 2024
BackgroundPressure injuries are a significant concern in clinical settings, requiring accurate assessment to prevent complications. Traditional assessment methods are often subjective and time-consuming.ObjectiveThis study aimed to develop and evalua...
Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach.
Diagnostic and interventional radiology (Ankara, Turkey)
Dec 9, 2024
PURPOSE: The purpose of this study was to propose a new computer-assisted two-staged diagnosis system that combines a modified deep learning (DL) architecture (VGG19) for the classification of digital breast tomosynthesis (DBT) images with the detect...
Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.
Journal of vascular and interventional radiology : JVIR
Dec 9, 2024
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...
Pneumothorax
Hemoptysis
Natural Language Processing
Humans
Middle Aged
Feasibility Studies
Female
Retrospective Studies
Time Factors
Neoplasm Recurrence, Local
Reproducibility of Results
Large Language Models
Electronic Health Records
Lung Neoplasms
Aged
Microwaves
Hemothorax
Treatment Outcome
Male
Recurrence
Ablation Techniques
Predictive Value of Tests
Data Mining
Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.
Medical & biological engineering & computing
Dec 9, 2024
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...
Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.
European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.
Journal of cardiothoracic and vascular anesthesia
Dec 9, 2024
OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.
Modeling the fasting blood glucose response to basal insulin adjustment in type 2 diabetes: An explainable machine learning approach on real-world data.
International journal of medical informatics
Dec 9, 2024
INTRODUCTION: Optimal basal insulin titration for people with type 2 diabetes is vital to effectively reducing the risk of complications. However, a sizeable proportion of people (30-50 %) remain in suboptimal glycemic control six months post-initiat...
Evaluation of the clinical utility of lateral cephalometry reconstructed from computed tomography extracted by artificial intelligence.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Dec 9, 2024
This study assessed the accuracy and reliability of artificial intelligence (AI)-reconstructed images of two-dimensional (2D) lateral cephalometric analyses of facial computed tomography (CT) images, which is widely used for the diagnosis of craniofa...
Prediction of Visual Acuity After Cataract Surgery by Deep Learning Methods Using Clinical Information and Color Fundus Photography.
Current eye research
Dec 9, 2024
PURPOSE: To examine the performance of deep-learning models that predicts the visual acuity after cataract surgery using preoperative clinical information and color fundus photography (CFP).
Artificial intelligence aided serum protein electrophoresis analysis of Finnish patient samples: Retrospective validation.
Clinica chimica acta; international journal of clinical chemistry
Dec 9, 2024
BACKGROUND AND AIMS: Serum protein electrophoresis interpretation requires a substantial amount of manual work. In 2020, Chabrun et al. created a machine learning method called SPECTR for the task. We aimed to validate and test the SPECTR method agai...
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