AIMC Topic: Retrospective Studies

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Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer.

Frontiers in endocrinology
OBJECTIVE: This study explores the value of combining intratumoral and peritumoral radiomics features from ultrasound imaging with clinical characteristics to assess axillary lymph node burden in breast cancer patients.

A deep learning-based psi CT network effectively predicts early recurrence after hepatectomy in HCC patients.

Abdominal radiology (New York)
BACKGROUND: Hepatocellular carcinoma (HCC) exhibits a high recurrence rate, and early recurrence significantly jeopardizes patient prognosis, necessitating reliable methods for early recurrence prediction.

Accuracy of 7 artificial intelligence-based intraocular lens power calculation formulas in medium-long eyes: 2-center study.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To compare accuracy of 7 artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in medium-long eyes DESIGN: Retrospective observational study.

Multi-parametric MRI Habitat Radiomics Based on Interpretable Machine Learning for Preoperative Assessment of Microsatellite Instability in Rectal Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: This study constructed an interpretable machine learning model based on multi-parameter MRI sub-region habitat radiomics and clinicopathological features, aiming to preoperatively evaluate the microsatellite instability (MSI...

Pre-transplant and transplant parameters predict long-term survival after hematopoietic cell transplantation using machine learning.

Transplant immunology
BACKGROUND: Allogeneic hematopoietic stem transplantation (allo-HSCT) constitutes a curative treatment for various hematological malignancies. However, various complications limit the therapeutic efficacy of this approach, increasing the morbidity an...

Deep Learning for Lumbar Disc Herniation Diagnosis and Treatment Decision-Making Using Magnetic Resonance Imagings: A Retrospective Study.

World neurosurgery
BACKGROUND: Lumbar disc herniation (LDH) is a common cause of back and leg pain. Diagnosis relies on clinical history, physical exam, and imaging, with magnetic resonance imaging (MRI) being an important reference standard. While artificial intellige...

Using Machine Learning to Improve Readmission Risk in Surgical Patients in South Africa.

International journal of environmental research and public health
Unplanned readmission within 30 days is a major challenge both globally and in South Africa. The aim of this study was to develop a machine learning model to predict unplanned surgical and trauma readmission to a public hospital in South Africa from ...

Early detection of feline chronic kidney disease via 3-hydroxykynurenine and machine learning.

Scientific reports
Feline chronic kidney disease (CKD) is one of the most frequently encountered diseases in veterinary practice, and the leading cause of mortality in cats over five years of age. While diagnosing advanced CKD is straightforward, current routine tests ...

Development and evaluation of a multivariable prediction model for overall survival in advanced stage pulmonary carcinoid using machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Evidence is limited on whether patients with advanced pulmonary carcinoid (APC) benefit from comprehensive pulmonary resection (CPR), chemotherapy, or radiotherapy. Existing prognostic models for APC are limited and do not guide treatment...