AIMC Topic: Aged

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Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms.

Frontiers in public health Feb 21, 2025
BACKGROUND: It has been increasingly recognized that adults living alone have a higher likelihood of developing Major Depressive Disorder (MDD) than those living with others. However, there is still no prediction model for MDD specifically designed f...
Depressive Disorder, Major Humans Risk Factors Nutrition Surveys Machine Learning Aged United States Algorithms Adult Female Male Middle Aged
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Early prediction of 30-day mortality in patients with surgical wound infections following cardiothoracic surgery: Development and validation of the SWICS-30 score utilizing conventional logistic regression and artificial neural network.

The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases Feb 21, 2025
INTRODUCTION: We aimed to create and validate the 30-day prognostic score for mortality in patients with surgical wound infection (SWICS-30) after cardiothoracic surgery.
Adolescent Hospital Mortality Logistic Models Cardiac Surgical Procedures Surgical Wound Infection Young Adult Humans Adult Male Neural Networks, Computer Middle Aged Prognosis Risk Assessment Retrospective Studies Female Risk Factors Aged Aged, 80 and over
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Plasma Cytokine and Chemokine Profiles Predict Efficacy and Toxicity of Anti-CD19 CAR-T Cell Therapy in Large B-Cell Lymphoma.

Clinical lymphoma, myeloma & leukemia Feb 20, 2025
BACKGROUND: Anti-CD19 chimeric antigen receptor T-cell (CAR-T) therapy has emerged as a promising treatment for large B-cell lymphoma (LBCL); however, durable complete responses are achieved in only 30% to 40% of patients. Additionally, CAR-T therapy...
Cytokines Female Aged Adult Receptors, Chimeric Antigen Humans Chemokines Immunotherapy, Adoptive Antigens, CD19 Lymphoma, Large B-Cell, Diffuse Male Middle Aged Treatment Outcome
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Diastolic Versus Systolic or Mean Intraoperative Hypotension as Predictive of Perioperative Myocardial Injury in a White-Box Machine-Learning Model.

Anesthesia and analgesia Feb 20, 2025
BACKGROUND: Intraoperative hypotension (IOH) and tachycardia are associated with perioperative myocardial injury (PMI), and thereby increased postoperative mortality. Patients undergoing vascular surgery are specifically at risk of developing cardiac...
Systole Intraoperative Complications Diastole Tachycardia Troponin T Hypotension Heart Rate Arterial Pressure Prospective Studies Female Risk Factors Aged Male Middle Aged Monitoring, Intraoperative Humans Predictive Value of Tests Blood Pressure Machine Learning
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Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging: a comprehensive deep learning study.

European journal of nuclear medicine and molecular imaging Feb 20, 2025
BACKGROUND: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a well-established modality for noninvasive diagnostic assessment of coronary artery disease (CAD). However, the time-consuming and experience-...
Humans Deep Learning Image Processing, Computer-Assisted Coronary Artery Disease Tomography, Emission-Computed, Single-Photon Myocardial Perfusion Imaging Artificial Intelligence Female Aged Male Middle Aged
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Artificial intelligence-based model to predict recurrence after local excision in T1 rectal cancer.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Feb 20, 2025
BACKGROUND: According to current guideline, patients with resected specimens showing high-risk features are recommended additional surgery after local excision (LE) of T1 colorectal cancer, despite the low incidence of recurrence. However, surgical r...
Rectal Neoplasms Proctectomy Retrospective Studies Female Aged Male Middle Aged Risk Assessment ROC Curve Neoplasm Staging Neoplasm Recurrence, Local Humans Neural Networks, Computer Artificial Intelligence
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System for Predicting Neurological Outcomes Following Cardiac Arrest Based on Clinical Predictors Using a Machine Learning Method: The Neurological Outcomes After Cardiac Arrest Method.

Neurocritical care Feb 20, 2025
BACKGROUND: A multimodal approach may prove effective for predicting clinical outcomes following cardiac arrest (CA). We aimed to develop a practical predictive model that incorporates clinical factors related to CA and multiple prognostic tests usin...
Prognosis Female Aged Male Middle Aged Humans Machine Learning Electroencephalography Outcome Assessment, Health Care Heart Arrest Glasgow Coma Scale
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Machine Learning-Driven Modeling to Predict Postdischarge Venous Thromboembolism After Pancreatectomy for Pancreas Cancer.

Annals of surgical oncology Feb 20, 2025
BACKGROUND: Postdischarge venous thromboembolism (pdVTE) is a life-threatening complication following resection for pancreatic cancer (PC). While national guidelines recommend extended chemoprophylaxis for all, adherence is low and ranges from 1.5 to...
Humans Machine Learning Prognosis Patient Discharge Retrospective Studies Venous Thromboembolism Middle Aged Pancreatectomy Postoperative Complications Follow-Up Studies Decision Trees Female Pancreatic Neoplasms Risk Factors Aged Male
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Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study.

American journal of ophthalmology Feb 20, 2025
PURPOSE: To utilize a convolutional neural network (CNN) to predict the response of treatment-naïve diabetic macular edema (DME) to a single injection of anti-vascular endothelial growth factor (anti-VEGF) with data from optical coherence tomography ...
Angiogenesis Inhibitors Treatment Outcome Follow-Up Studies Visual Acuity Tomography, Optical Coherence Male Middle Aged Convolutional Neural Networks Humans Pilot Projects Bevacizumab Diabetic Retinopathy Neural Networks, Computer Macular Edema Retrospective Studies Vascular Endothelial Growth Factor A Female Intravitreal Injections Aged Ranibizumab
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T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study.

Journal of applied clinical medical physics Feb 20, 2025
PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).
Magnetic Resonance Imaging Humans Rectal Neoplasms Retrospective Studies Middle Aged Female Deep Learning Aged Imaging, Three-Dimensional Aged, 80 and over Image Processing, Computer-Assisted Adult Male
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