AIMC Topic: Retrospective Studies

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Prediction of peripheral blood lymphocyte subpopulations after renal transplantation.

Renal failure
Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). Peripheral blood lymphocyte subpopulations (PBLSs) are widely used biomarkers for immune monitoring, yet there is no established standard reference fo...

Prediction of Poor Visual Outcomes at Idiopathic Intracranial Hypertension Diagnosis Using a Supervised Machine Learning Algorithm.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: Idiopathic intracranial hypertension (IIH) is a vision-threatening disorder mainly affecting women of a reproductive age. Prompt diagnosis and intervention are vital to prevent vision loss, but validated tools to predict visual outcomes a...

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 ...

Human versus machine: deciding on high-stakes surgery in possible cauda equina syndrome.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Cauda equina syndrome (CES) is a spine surgical urgency requiring prompt intervention to prevent neurological deficits. Accurate identification of CES cases needing urgent surgery is essential to avoid long-term sequelae.

Development of a novel machine learning model to automate vertebral column segmentation utilizing biplanar full-body imaging.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Degenerative scoliosis (DS) is a common spinal disorder among adults, characterized by lateral curvature of the spine. Recent advancements in biplanar full-body imaging, a low-dose and weight-bearing X-ray modality, facilitate saf...

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...

Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.

Renal failure
BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD prediction are urgently needed. This study aimed to set up DKD risk prediction models based on machine lear...

Machine learning models for prediction of NPVR ≥80% with HIFU ablation for uterine fibroids.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
BACKGROUND: Currently high-intensity focused ultrasound (HIFU) is widely used to treat uterine fibroids (UFs). The aim of this study is to develop a machine learning model that can accurately predict the efficacy of HIFU ablation for UFs, assisting t...