AIMC Topic: Recurrence

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Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study.

The Journal of dermatological treatment
BACKGROUND: Identifying the risk of psoriasis relapse after discontinuing biologics can help optimize treatment strategies, potentially reducing relapse rates and alleviating the burden of disease management.

An AI model classifies risks of early relapse post-CAR T-cell therapy in a multicenter real-world population with DLBCL.

Blood advances
Accumulating real-world (RW) evidence of axicabtagene ciloleucel (axi-cel) has demonstrated comparable performance to that of pivotal trials. However, ∼57% of patients eventually relapse, with most requiring additional therapies. Being able to identi...

The risk factors for relapse behavior in individuals with substance use disorders: An interpretable machine learning study.

Journal of affective disorders
BACKGROUND: Substance abuse has become a serious public health problem worldwide, and finding effective prevention and treatment strategies is undoubtedly an urgent need. This study addresses the risk factors that lead to relapse behaviors among subs...

Peripheral HLA-DRCD141 Classical Monocytes Predict Relapse Risk and Worsening in Multiple Sclerosis.

Neurology(R) neuroimmunology & neuroinflammation
BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the CNS characterized by a heterogeneous disease trajectory, highlighting the need for biomarkers to predict disease activity. Current disease-monitorin...

Predicting the Recurrence of Sporadic Odontogenic Keratocyst Using Whole-Slide Histopathology Images With the Hybrid Encoder Iterative Attention Convolution Model.

Clinical and experimental dental research
OBJECTIVES: Odontogenic keratocysts (OKCs) are challenging due to their aggressiveness and high recurrence rates, complicating decision-making for clinicians and pathologists. Despite efforts to identify predictive characteristics, management remains...

Risk prediction models for patients with recurrent diabetic foot ulcers: A systematic review.

Public health
OBJECTIVES: To systematically review published studies on risk prediction models for patients with recurrent diabetic foot ulcers.

Prediction of endoscopic restenosis after endoscopic balloon dilation in patients with Crohn's disease: a machine learning approach.

Surgical endoscopy
BACKGROUND: Endoscopic balloon dilation (EBD) is recognized as a minimally invasive and effective procedure for managing intestinal stenosis in patients with Crohn's disease (CD). It offers an alternative to surgery and has been shown to improve the ...

Visceral Fat Quantified by a Fully Automated Deep-Learning Algorithm and Risk of Incident and Recurrent Diverticulitis.

Diseases of the colon and rectum
BACKGROUND: Obesity is a risk factor for diverticulitis. However, it remains unclear whether visceral fat area, a more precise measurement of abdominal fat, is associated with the risk of diverticulitis.

Deep learning radiomics of left atrial appendage features for predicting atrial fibrillation recurrence.

BMC medical imaging
BACKGROUND: Structural remodeling of the left atrial appendage (LAA) is characteristic of atrial fibrillation (AF), and LAA morphology impacts radiofrequency catheter ablation (RFCA) outcomes. In this study, we aimed to develop and validate a predict...

A Multidimensional Regression Model for Predicting Recurrence in Chronic Low Back Pain.

European journal of pain (London, England)
BACKGROUND: Recurrence is common in chronic low back pain (CLBP). However, predicting the recurrence risk remains a challenge. The aim is to develop and validate a machine learning tool to predict the recurrence risk in patients with CLBP by using mu...