AIMC Topic: Middle Aged

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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...
Aged Adult Breast Neoplasms Middle Aged Radiographic Image Interpretation, Computer-Assisted Breast Deep Learning Mammography Humans Female
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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...
Middle Aged Time Factors Lung Neoplasms Treatment Outcome Feasibility Studies Neoplasm Recurrence, Local Data Mining Predictive Value of Tests Natural Language Processing Female Reproducibility of Results Aged Male Humans Retrospective Studies Ablation Techniques Microwaves Electronic Health Records Pneumothorax Recurrence Large Language Models Hemothorax Hemoptysis
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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...
Risk Factors Aged Male Middle Aged Reoperation Risk Assessment Arthroplasty, Replacement, Knee Humans Machine Learning Female
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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 ...
Risk Factors Aged Aged, 80 and over Male Machine Learning Algorithms Retrospective Studies Female Predictive Value of Tests Humans Aortic Aneurysm, Abdominal Elective Surgical Procedures Random Forest Endovascular Procedures Middle Aged Risk Assessment Time Factors Treatment Outcome
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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.
Risk Assessment Postoperative Complications Cohort Studies Systemic Inflammatory Response Syndrome Risk Factors Humans Aged Predictive Value of Tests Machine Learning Male Cardiac Surgical Procedures Retrospective Studies Middle Aged Female
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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...
Blood Glucose Insulin Diabetes Mellitus, Type 2 Hypoglycemic Agents Humans Aged Machine Learning Male Female Middle Aged Fasting
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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...
Observer Variation Adolescent Image Processing, Computer-Assisted Anatomic Landmarks Cephalometry Artificial Intelligence Algorithms Tomography, X-Ray Computed Female Adult Humans Reproducibility of Results Male Young Adult Middle Aged
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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).
Aged Aged, 80 and over Male Middle Aged Deep Learning Humans Retrospective Studies Female Postoperative Period Photography Visual Acuity Cataract Extraction Cataract Fundus Oculi
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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...
Blood Protein Electrophoresis Humans Female Middle Aged Neural Networks, Computer Male Blood Proteins Artificial Intelligence Finland Retrospective Studies
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Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.

International journal of computer assisted radiology and surgery Dec 9, 2024
PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions, particularly speech, during tumor resection. The ability to accurately assess linguistic functions in real-time not only enhances surgical precision...
Middle Aged Deep Learning Wakefulness Craniotomy Aged Adult Brain Neoplasms Male Speech Disorders Humans Female
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