OBJECTIVES: This study investigated the impact of human-large language model (LLM) collaboration on the accuracy and efficiency of brain MRI differential diagnosis.
OBJECTIVE: The objective of this study is to investigate the value of radiomics features and deep learning features based on positron emission tomography/computed tomography (PET/CT) in predicting perineural invasion (PNI) in rectal cancer.
OBJECTIVES: To investigate the predictive value of the quantitative T2-FLAIR mismatch ratio (qT2FM) with fully automated tumor segmentation in adult-type diffuse lower-grade gliomas (LGGs).
OBJECTIVES: To evaluate the benefits of an automated deep learning-based tool (RTLI-DM) for early detection of radiation-induced temporal lobe injury (RTLI) on MRI.
: This study aims to evaluate the predictive value of comprehensive data obtained in obstetric clinics for the detection of stillbirth and the predictive ability set of machine learning models for stillbirth. : The study retrospectively included all ...
BACKGROUND AND OBJECTIVE: Spread through air spaces (STAS) is an important factor in determining the aggressiveness and recurrence risk of lung cancer, especially in early-stage adenocarcinoma. Preoperative identification of STAS is crucial for optim...
OBJECTIVE: The majority of individuals with hearing loss worldwide reside in low- and middle-income countries (LMICs), but there is limited information regarding the characteristics of hearing loss in these regions. This descriptive study aims to add...
BACKGROUND: To explore the predictive value of radiomics features extracted from anatomical ROIs in differentiating the International Society of Urological Pathology (ISUP) grading in prostate cancer patients.
OBJECTIVE: To develop a machine learning (ML) algorithm capable of identifying children at risk of out-of-home placement among a Medicaid-insured population.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 6, 2025
Automatic clinical tumor volume (CTV) delineation is pivotal to improving outcomes for interstitial brachytherapy cervical cancer. However, the prominent differences in gray values due to the interstitial needles bring great challenges on deep learni...
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