AIMC Topic: Nomograms

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Explaining Support Vector Machines: A Color Based Nomogram.

PloS one
PROBLEM SETTING: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine ...

Transversus abdominis plane block in robotic gynecologic oncology: a randomized, placebo-controlled trial.

Gynecologic oncology
OBJECTIVE: Although robotic surgery decreases pain compared to laparotomy, postoperative pain can be a concern near the site of a larger assistant trocar site. The aim of this study was to determine the efficacy of transversus abdominis plane (TAP) b...

Predicting high lymph node positivity risk factors in nasopharyngeal carcinoma patients: A multi-model approach.

Medicine
Identifying patients at high risk of an elevated lymph node ratio (LNR) is critical for optimizing the management of nasopharyngeal carcinoma (NPC), as LNR, defined as the ratio of metastatic to examined lymph nodes, serves as a key prognostic indica...

Personalized prediction of post-SMILE refractive outcomes using a machine-learning nomogram.

Medicine
This study aimed to construct a personalized, machine learning-driven nomogram capable of predicting refractive outcomes following small incision lenticule extraction (SMILE). A total of 1253 eyes from 632 patients who underwent SMILE to correct myop...

Predicting survival outcomes in renal cell carcinoma spinal metastases: a multicenter evaluation of existing prognostic systems.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Survival prediction models for patients with spinal metastases are crucial for guiding clinical decision-making and optimizing treatment strategies. Renal cell carcinoma spinal metastases (RCC-SM) present unique challenges due to ...

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

Renal failure
OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model...

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.