AIMC Topic: Retrospective Studies
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Individual and integrated indexes of inflammation predicting the risks of mental disorders - statistical analysis and artificial neural network.
BMC psychiatry
Mar 11, 2025
OBJECTIVE: The prevalence of mental illness in Taiwan increased. Identifying and mitigating risk factors for mental illness is essential. Inflammation may be a risk factor for mental illness; however, the predictive power of inflammation test values ...
Development and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study.
BMC gastroenterology
Mar 11, 2025
BACKGROUND: The aim of this study was to develop and internally validate an interpretable machine learning (ML) model for predicting the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) infection.
A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.
European journal of pediatrics
Mar 11, 2025
UNLABELLED: Congenital diaphragmatic hernia (CDH) has high morbidity and mortality rates. This study aimed to develop a machine learning (ML) algorithm to predict outcomes based on prenatal and early postnatal data. This retrospective observational c...
AI classification of knee prostheses from plain radiographs and real-world applications.
European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Mar 11, 2025
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...
Automated detection of small hepatocellular carcinoma in cirrhotic livers: applying deep learning to Gd-EOB-DTPA-enhanced MRI.
Abdominal radiology (New York)
Mar 10, 2025
OBJECTIVES: To develop an automated deep learning (DL) methodology for detecting small hepatocellular carcinoma (sHCC) in cirrhotic livers, leveraging Gd-EOB-DTPA-enhanced MRI.
Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.
The international journal of cardiovascular imaging
Mar 10, 2025
Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive coronary angiography (CAG), possibly outperforming humans, but has seldom been explored, especially for...
A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 10, 2025
BACKGROUND: To construct and assess a deep learning (DL) signature that employs computed tomography imaging to predict the expression status of programmed cell death ligand 1 in patients with bladder cancer (BCa).
Artificial Intelligence for Teaching Case Curation: Evaluating Model Performance on Imaging Report Discrepancies.
Academic radiology
Mar 9, 2025
RATIONALE AND OBJECTIVES: Assess the feasibility of using a large language model (LLM) to identify valuable radiology teaching cases through report discrepancy detection.
Using Natural Language Processing in the LACE Index Scoring Tool to Predict Unplanned Trauma and Surgical Readmissions in South Africa.
World journal of surgery
Mar 9, 2025
BACKGROUND: Unplanned and potentially avoidable readmission within 30 days post discharge is a major financial burden.
Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.
Nutrients
Mar 8, 2025
: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM ...
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