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Enhancing clinical decision-making in closed pelvic fractures with machine learning models.
Biomolecules & biomedicine
May 8, 2025
Closed pelvic fractures can lead to severe complications, including hemodynamic instability (HI) and mortality. Accurate prediction of these risks is crucial for effective clinical management. This study aimed to utilize various machine learning (ML)...
Developing the DigIQ: A measure of digital competence.
PloS one
May 8, 2025
Digital competence reflects the skills and knowledge needed to thrive in the digital world. Despite the criticality of this concept, the field lacks a robust and valid measure of digital competence that is suitable across the life span. Addressing th...
Radiomic analysis based on machine learning of multi-sequences MR to assess early treatment response in locally advanced nasopharyngeal carcinoma.
Science progress
May 8, 2025
ObjectiveThe prediction of early response in locally advanced nasopharyngeal carcinoma (LA-NPC) after concurrent chemoradiotherapy (CCRT) is important for determining the need for timely consolidation therapy. We developed a radiomic analysis of mult...
A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study.
BMC medicine
May 7, 2025
BACKGROUND: CT images and circulating tumor cells (CTCs) are indispensable for diagnosing the mediastinal lesions by providing radiological and intra-tumoral information. This study aimed to develop and validate a deep multimodal fusion network (DMFN...
Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data.
BMJ open
May 7, 2025
OBJECTIVES: To develop and validate a machine learning (ML) model to differentiate malignant from benign thyroid nodules (TNs) based on the routine data and provide diagnostic assistance for medical professionals.
Construction of exosome non-coding RNA feature for non-invasive, early detection of gastric cancer patients by machine learning: a multi-cohort study.
Gut
May 7, 2025
BACKGROUND AND OBJECTIVE: Gastric cancer (GC) remains a prevalent and preventable disease, yet accurate early diagnostic methods are lacking. Exosome non-coding RNAs (ncRNAs), a type of liquid biopsy, have emerged as promising diagnostic biomarkers f...
Optimizing Strategy for Lung Cancer Screening: From Risk Prediction to Clinical Decision Support.
JCO clinical cancer informatics
May 7, 2025
PURPOSE: Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the associated risks of subsequent invasive diagn...
Annotation-Free Whole-Slide Image Analysis Method to Assess Immune Infiltration in Colorectal Cancer.
JCO precision oncology
May 7, 2025
PURPOSE: Tumor-infiltrating lymphocytes (TILs) play a crucial role in host antitumor processes. High level of TILs is associated with better outcomes for patients. We aim to automatically quantify TILs without any nuclei annotation and further constr...
Explainable Machine Learning Models for Colorectal Cancer Prediction Using Clinical Laboratory Data.
Cancer control : journal of the Moffitt Cancer Center
May 7, 2025
IntroductionEarly diagnosis of colorectal cancer (CRC) poses a significant clinical challenge. This study aims to develop machine learning (ML) models for CRC risk prediction using clinical laboratory data.MethodsThis retrospective, single-center stu...
Stacking classifiers based on integrated machine learning model: fusion of CT radiomics and clinical biomarkers to predict lymph node metastasis in locally advanced gastric cancer patients after neoadjuvant chemotherapy.
BMC cancer
May 6, 2025
BACKGROUND: The early prediction of lymph node positivity (LN+) after neoadjuvant chemotherapy (NAC) is crucial for optimizing individualized treatment strategies. This study aimed to integrate radiomic features and clinical biomarkers through machin...
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