AIMC Topic: Predictive Value of Tests
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Multiparametric MRI-Based Deep Learning Models for Preoperative Prediction of Tumor Deposits in Rectal Cancer and Prognostic Outcome.
Academic radiology
Oct 22, 2024
RATIONALE AND OBJECTIVES: To investigate the predictive value of a deep learning model based on multiparametric MRI (mpMRI) for tumor deposit (TD) in rectal cancer (RC) patients and to analyze their prognosis.
ChatGPT-4 extraction of heart failure symptoms and signs from electronic health records.
Progress in cardiovascular diseases
Oct 21, 2024
BACKGROUND: Natural language processing (NLP) can facilitate research utilizing data from electronic health records (EHRs). Large language models can potentially improve NLP applications leveraging EHR notes. The objective of this study was to assess...
Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.
European journal of radiology
Oct 19, 2024
PURPOSE: To develop a predictive model combining clinical, radiomic, and deep learning features based on X-ray and MRI to identify risk factors for early femoral head deformity in Legg-Calvé-Perthes disease (LCPD).
Machine learning-based CT radiomics approach for predicting occult peritoneal metastasis in advanced gastric cancer preoperatively.
Clinical radiology
Oct 18, 2024
AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients.
Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.
Journal of human hypertension
Oct 18, 2024
Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascular disease (CVD). Artificial intelligence-based analysis of 12-lead electrocardiograms (ECGs) can already detect arrhythmias and hypertension. We perf...
Harnessing machine learning technique to authenticate differentially expressed genes in oral squamous cell carcinoma.
Oral surgery, oral medicine, oral pathology and oral radiology
Oct 17, 2024
OBJECTIVE: Advancements in early detection of the disease, prognosis and the development of therapeutic strategies necessitate tumor-specific biomarkers. Despite continuous efforts, no molecular marker has been proven to be an effective therapeutic t...
Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.
Annals of vascular surgery
Oct 16, 2024
BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural language processing (NLP) offers a promising solution to address these issues. While rule-based NLP meth...
A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients.
Academic radiology
Oct 15, 2024
RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the capability of an ultrasound (US)-based deep learning (DL) nomogram for predicting axillary lymph node (ALN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients and ...
Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.
Tuberculosis (Edinburgh, Scotland)
Oct 11, 2024
OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accurate diagnosis challenging. This study aims to identify TB diagnostic biomarkers by integrating gene e...
Machine Learning Model for Predicting Risk Factors of Prolonged Length of Hospital Stay in Patients with Aortic Dissection: a Retrospective Clinical Study.
Journal of cardiovascular translational research
Oct 10, 2024
The length of hospital stay (LOS) is crucial for assessing medical service quality. This study aimed to develop machine learning models for predicting risk factors of prolonged LOS in patients with aortic dissection (AD). The data of 516 AD patients ...
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