AIMC Topic: Retrospective Studies
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Novel deep learning algorithm based MRI radiomics for predicting lymph node metastases in rectal cancer.
Scientific reports
Apr 9, 2025
To explore the value of applying the MRI-based radiomic nomogram for predicting lymph node metastasis (LNM) in rectal cancer (RC). This retrospective analysis used data from 430 patients with RC from two medical centers. The patients were categorized...
A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation.
Journal of medical Internet research
Apr 9, 2025
BACKGROUND: Postoperative acute kidney injury (AKI) is a significant risk associated with surgeries under general anesthesia, often leading to increased mortality and morbidity. Existing predictive models for postoperative AKI are usually limited to ...
Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study.
Journal of medical Internet research
Apr 9, 2025
BACKGROUND: Considering that most patients with low or no significant risk factors can safely undergo noncardiac surgery without additional cardiac evaluation, and given the excessive evaluations often performed in patients undergoing intermediate or...
Cross-institutional validation of a polar map-free 3D deep learning model for obstructive coronary artery disease prediction using myocardial perfusion imaging: insights into generalizability and bias.
European journal of nuclear medicine and molecular imaging
Apr 8, 2025
PURPOSE: Deep learning (DL) models for predicting obstructive coronary artery disease (CAD) using myocardial perfusion imaging (MPI) have shown potential for enhancing diagnostic accuracy. However, their ability to maintain consistent performance acr...
Development and validation of Prediction models for radiation-induced hypoglossal neuropathy in patients with nasopharyngeal carcinoma.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 8, 2025
BACKGROUND AND PURPOSE: To establish predictive models for radiation-induced hypoglossal neuropathy (RIHN) in patients with nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).
Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mellitus.
Acta cardiologica
Apr 8, 2025
BACKGROUND: Predicting the prognosis of patients with acute myocardial infarction (AMI) combined with diabetes mellitus (DM) is crucial due to high in-hospital mortality rates. This study aims to develop and validate a mortality risk prediction model...
Application of machine learning in assessing disease activity in SLE.
Lupus science & medicine
Apr 8, 2025
OBJECTIVE: SLE is a chronic autoimmune disease with immune complex deposition in various organs, causing inflammation. The Systemic Lupus Erythematosus Disease Activity Index 2000 assesses disease severity but is subjective. This study aimed to const...
Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.
Renal failure
Apr 7, 2025
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...
Predicting postoperative complications after pneumonectomy using machine learning: a 10-year study.
Annals of medicine
Apr 7, 2025
BACKGROUND: Reducing postoperative cardiovascular and neurological complications (PCNC) during thoracic surgery is the key to improving postoperative survival.
Skull CT metadata for automatic bone age assessment by using three-dimensional deep learning framework.
International journal of legal medicine
Apr 7, 2025
Bone age assessment (BAA) means challenging tasks in forensic science especially in some extreme situations like only skulls found. This study aimed to develop an accurate three-dimensional deep learning (DL) framework at skull CT metadata for BAA an...
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