AIMC Topic: Recurrence
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Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review.
BMJ open
Feb 25, 2025
OBJECTIVES: We aimed to examine the predictive accuracy of functioning, relapse or remission among patients with psychotic disorders, using machine learning methods. We also identified specific features that were associated with these clinical outcom...
Machine learning-based prediction model for patients with recurrent Staphylococcus aureus bacteremia.
BMC medical informatics and decision making
Feb 24, 2025
BACKGROUND: Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both community-acquired and healthcare-associated bloodstream infections. SAB exhibits a high recurrence rate and mortality rate, leading to numerous clinical tre...
Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach.
JMIR cardio
Feb 11, 2025
BACKGROUND: Atrial fibrillation (AF) is a prevalent arrhythmia associated with significant morbidity and mortality. Despite advancements in ablation techniques, predicting recurrence of AF remains a challenge, necessitating reliable models to identif...
A recurrence model for non-puerperal mastitis patients based on machine learning.
PloS one
Jan 16, 2025
OBJECTIVE: Non-puerperal mastitis (NPM) is an inflammatory breast disease affecting women during non-lactation periods, and it is prone to relapse after being cured. Accurate prediction of its recurrence is crucial for personalized adjuvant therapy, ...
Machine learning-based prediction of illness course in major depression: The relevance of risk factors.
Journal of affective disorders
Jan 14, 2025
BACKGROUND: Major depressive disorder (MDD) comes along with an increased risk of recurrence and poor course of illness. Machine learning has recently shown promise in the prediction of mental illness, yet models aiming to predict MDD course are stil...
Development of Time-Aggregated Machine Learning Model for Relapse Prediction in Pediatric Crohn's Disease.
Clinical and translational gastroenterology
Jan 1, 2025
INTRODUCTION: Pediatric Crohn's disease (CD) easily progresses to an active disease compared with adult CD, making it important to predict and minimize CD relapses. However, prediction of relapse at various time points (TPs) during pediatric CD remai...
Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.
Journal of cardiovascular electrophysiology
Dec 23, 2024
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates partly due to the considerable heterogeneity within the patient population. Identifying distinct patient phenotypes based on post-ablation prognosis co...
Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.
BMC cardiovascular disorders
Dec 19, 2024
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machi...
Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Dec 17, 2024
OBJECTIVE: This study aims to develop an interpretable machine learning (ML) predictive model to assess its efficacy in predicting postoperative recurrence in pediatric chronic rhinosinusitis (CRS).
TransformerLSR: Attentive joint model of longitudinal data, survival, and recurrent events with concurrent latent structure.
Artificial intelligence in medicine
Dec 16, 2024
In applications such as biomedical studies, epidemiology, and social sciences, recurrent events often co-occur with longitudinal measurements and a terminal event, such as death. Therefore, jointly modeling longitudinal measurements, recurrent events...
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