AIMC Topic: Treatment Outcome
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Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.
Journal of vascular and interventional radiology : JVIR
Aug 28, 2024
PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical ...
Predictive Value of Tests
Neoplasm Staging
Radiographic Image Interpretation, Computer-Assisted
Neoplasm Recurrence, Local
Microwaves
Margins of Excision
Adenocarcinoma of Lung
Ablation Techniques
Decision Support Techniques
Middle Aged
Retrospective Studies
Risk Assessment
Tomography, X-Ray Computed
Time Factors
Clinical Decision-Making
Lung Neoplasms
Female
Treatment Outcome
Humans
Machine Learning
Risk Factors
Aged
Radiomics
Male
Meta-analysis of the effectiveness of early endoscopic treatment of Acute biliary pancreatitis based on lightweight deep learning model.
BMC gastroenterology
Aug 28, 2024
BACKGROUND: Acute biliary pancreatitis (ABP) is a clinical common acute abdomen. After the first pancreatitis, relapse rate is high, which seriously affects human life and health and causes great economic burdens to family and society. According to a...
Prediction of treatment outcome for branch retinal vein occlusion using convolutional neural network-based retinal fluorescein angiography.
Scientific reports
Aug 28, 2024
Deep learning techniques were used in ophthalmology to develop artificial intelligence (AI) models for predicting the short-term effectiveness of anti-VEGF therapy in patients with macular edema secondary to branch retinal vein occlusion (BRVO-ME). 1...
Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.
Journal of the American Heart Association
Aug 27, 2024
BACKGROUND: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke o...
Predictors of residual tricuspid regurgitation after interventional therapy: an automated deep-learning CT analysis.
Scientific reports
Aug 27, 2024
Computed tomography (CT) is used as a valuable tool for device selection for interventional therapy in tricuspid regurgitation (TR). We aimed to evaluate predictors of TR reduction using CT and automated deep learning algorithms. Patients with severe...
Advanced rehabilitation in ischaemic stroke research.
Stroke and vascular neurology
Aug 27, 2024
At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physic...
Machine learning assessment of vildagliptin and linagliptin effectiveness in type 2 diabetes: Predictors of glycemic control.
PloS one
Aug 26, 2024
OBJECTIVE: Differential effects of linagliptin and vildagliptin may help us personalize treatment for Type 2 Diabetes Mellitus (T2DM). The current study compares the effect of these drugs on glycated hemoglobin (HbA1c) in an artificial neural network...
Health inequities, bias, and artificial intelligence.
Techniques in vascular and interventional radiology
Aug 24, 2024
Musculoskeletal (MSK) pain leads to significant healthcare utilization, decreased productivity, and disability globally. Due to its complex etiology, MSK pain is often chronic and challenging to manage effectively. Disparities in pain management-infl...
Advancing toward precision migraine treatment: Predicting responses to preventive medications with machine learning models based on patient and migraine features.
Headache
Aug 23, 2024
OBJECTIVE: To develop machine learning models using patient and migraine features that can predict treatment responses to commonly used migraine preventive medications.
Artificial Intelligence-Assisted Speech Therapy for /ɹ/: A Single-Case Experimental Study.
American journal of speech-language pathology
Aug 22, 2024
PURPOSE: This feasibility trial describes changes in rhotic production in residual speech sound disorder following ten 40-min sessions including artificial intelligence (AI)-assisted motor-based intervention with ChainingAI, a version of Speech Motor...
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