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Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning.
BMC infectious diseases
Jul 1, 2025
OBJECTIVE: To develop and validate a novel diagnostic model for detecting bacterial infections in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) using advanced machine learning algorithms. The focus is on improving ...
Validation of an AI-enabled exome/transcriptome liquid biopsy platform for early detection, MRD, disease monitoring, and therapy selection for solid tumors.
Scientific reports
Jul 1, 2025
Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring of disease burden. Caris Assure is a multifunctional blood-based assay that couples whole exome and w...
Comparative analysis of ChatGPT 3.5 and ChatGPT 4 obstetric and gynecological knowledge.
Scientific reports
Jul 1, 2025
Generative Pretrained Transformer (GPT) is one of the most ubiquitous large language models (LLMs), employing artificial intelligence (AI) to generate human-like language. Although the use of ChatGPT has been evaluated in different medical specialtie...
Artificial intelligence outperforms humans in morphology-based oocyte selection in cattle.
Scientific reports
Jul 1, 2025
Evaluating cumulus-oocyte complex (COC) morphology is commonly used to assess oocyte quality. However, clear guidelines on interpreting COC morphology data are lacking as this evaluation method is subjective. In the present study, individual in vitro...
Muscle-Driven prognostication in gastric cancer: A multicenter deep learning framework integrating Iliopsoas and erector spinae radiomics for 5-Year survival prediction.
Scientific reports
Jul 1, 2025
This study developed a 5-year survival prediction model for gastric cancer patients by combining radiomics and deep learning, focusing on CT-based 2D and 3D features of the iliopsoas and erector spinae muscles. Retrospective data from 705 patients ac...
Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.
Scientific reports
Jul 1, 2025
Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal clinical records. The motivation stems from the need for timely medical resource allocation, improved ...
Leveraging an ensemble of EfficientNetV1 and EfficientNetV2 models for classification and interpretation of breast cancer histopathology images.
Scientific reports
Jul 1, 2025
Breast cancer is the second leading cause of cancer-related deaths among women, following lung cancer, as of 2024. Conventional cancer diagnosis relies on the manual examination of biopsied tissues by pathologists, a time-consuming process that may v...
Development of a machine learning model to identify the predictors of the neonatal intensive care unit admission.
Scientific reports
Jul 1, 2025
Scientists aim to create a system that can predict the likelihood of newborns being admitted to the neonatal intensive care unit (NICU) by combining various statistical methods. This prediction could potentially reduce the negative health outcomes, d...
A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.
Scientific reports
Jul 1, 2025
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...
Development and evaluation of an automated classification and counting system for rice planthoppers captured on survey boards.
Scientific reports
Jul 1, 2025
Rice planthoppers are the most economically important insect pests of rice in Asia. Traditional surveys to examine their abundance and composition in paddy fields involve human visual inspection, which requires considerable time and effort by expert ...
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