AIMC Topic: Cohort Studies

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Factors Contributing to Early Recovery of Urinary Continence Analyzed by Pre- and Postoperative Pelvic Anatomical Features at Robot-Assisted Laparoscopic Radical Prostatectomy.

Journal of endourology
OBJECTIVE: The aim of the present study is to elucidate factors contributing to early recovery of urinary continence after robot-assisted laparoscopic radical prostatectomy (RARP) from the perspective of urethral and vesical anatomical features after...

Secondary use of electronic health records for building cohort studies through top-down information extraction.

Journal of biomedical informatics
Controlled clinical trials are usually supported with an in-front data aggregation system, which supports the storage of relevant information according to the trial context within a highly structured environment. In contrast to the documentation of c...

Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods.

Medical decision making : an international journal of the Society for Medical Decision Making
BACKGROUND: Multiple embryo transfers in in vitro fertilization (IVF) treatment increase the number of successful pregnancies while elevating the risk of multiple gestations. IVF-associated multiple pregnancies exhibit significant financial, social, ...

Machine learning-driven prediction of readmission risk in heart failure patients with diabetes: synergistic assessment of inflammatory and metabolic biomarkers.

International journal of cardiology
BACKGROUND: Heart failure (HF) and diabetes mellitus (DM) frequently coexist, exacerbating disease progression and increasing hospital readmission risk. Accurate prediction of readmission in HF patients with DM remains a clinical challenge. This stud...

Combined magnetic resonance imaging and serum analysis reveals distinct multiple sclerosis types.

Brain : a journal of neurology
Multiple sclerosis (MS) is a highly heterogeneous disease in its clinical manifestation and progression. Predicting individual disease courses is key for aligning treatments with underlying pathobiology. We developed an unsupervised machine learning ...

Fecal gut microbiota and amino acids as noninvasive diagnostic biomarkers of Pediatric inflammatory bowel disease.

Gut microbes
BACKGROUND AND AIMS: Fecal calprotectin (FCP) has limited specificity as diagnostic biomarker of pediatric inflammatory bowel disease (IBD), leading to unnecessary invasive endoscopies. This study aimed to develop and validate a fecal microbiota and ...

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.