International journal of surgery (London, England)
Sep 1, 2024
BACKGROUND: The accuracy of traditional clinical methods for assessing the metastatic status of axillary lymph nodes (ALNs) is unsatisfactory. In this study, the authors propose the use of radiomic technology and three-dimensional (3D) visualization ...
BACKGROUND & AIMS: The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists after hepatitis B surface antigen (HBsAg) seroclearance. This study aimed to develop and validate a machine learning model to predict the risk of liver-...
Journal of the European Academy of Dermatology and Venereology : JEADV
Aug 31, 2024
BACKGROUND: The broad histomorphological spectrum of melanocytic pathologies requires large data sets to develop accurate and generalisable deep learning (DL)-based diagnostic pathology classifiers. Weakly supervised DL promotes utilisation of larger...
OBJECTIVES: This study aimed to investigate the influence of baseline sarcopenia and changes in body composition on survival during cervical cancer treatment.
BACKGROUND: We aimed to determine the best-performing machine learning (ML)-based algorithm for predicting gestational diabetes mellitus (GDM) with sociodemographic and obstetrics features in the pre-conceptional period.
Journal of preventive medicine and hygiene
Aug 31, 2024
BACKGROUND: Low survival rates of breast cancer in developing countries are mainly due to the lack of early detection plans and adequate diagnosis and treatment facilities.
OBJECTIVES: This study aims to assess the performance of a multimodal artificial intelligence (AI) model capable of analyzing both images and textual data (GPT-4V), in interpreting radiological images. It focuses on a range of modalities, anatomical ...
OBJECTIVES: This study aimed to utilize MR radiomics-based machine learning classifiers on a large-sample, multicenter dataset to develop an optimal model for predicting malignant sinonasal tumors and tumor-like lesions.
OBJECTIVE: To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference Machines (CIRIM) with respect to image quality and reconstruction times when 12-fold accelerated scans of patients with neurological deficits are reco...
RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before treatment is important for selecting the appropriate treatment groups, formulating individualized treatment plans, and improving the survival rates of pa...
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