AIMC Topic: Female

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Diagnostic Machine Learning Models of Infectious Mononucleosis in Children Based on Clinical Data: A Retrospective Multicenter Study.

Journal of medical virology
The clinical manifestations of infectious mononucleosis (IM) and acute respiratory tract infections (ARTI) exhibit significant similarities. We aim to develop cost-efficient models for IM in children utilizing the Shapley Additive explanation (SHAP) ...

Updates and advances for gynecologic imaging.

The journal of obstetrics and gynaecology research
A gynecologic malignancy is one of the most common cancers affecting females and is responsible for significant rates of morbidity and mortality throughout the world. Early discovery and accurate staging, as well as early recurrence detection and cor...

Developing an Explainable Prognostic Model for Acute Ischemic Stroke: Combining Clinical and Inflammatory Biomarkers With Machine Learning.

Brain and behavior
BACKGROUND: Predicting the prognosis of patients with acute cerebral infarction (ACI) is crucial for clinical decision-making and personalized treatment. However, existing models often lack the comprehensive integration of clinical and biological ind...

Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.

Korean journal of radiology
OBJECTIVE: To evaluate the effect of deep learning (DL)-based artificial intelligence (AI) software on the diagnostic performance of radiologists with different experience levels in detecting nigrosome 1 (N1) abnormalities on susceptibility map-weigh...

The Critical Role of APOE+ Macrophages in the Immune Microenvironment and Prognosis of Lung Adenocarcinoma.

Journal of cellular and molecular medicine
The immunoregulatory functions and clinical implications of APOE+ macrophages within the tumour microenvironment of lung adenocarcinoma remain incompletely defined. In this study, single-cell transcriptome analysis revealed distinct subsets of APOE+ ...

Using Machine Learning to Improve Control for Confounding in the Dynamic Weighted Ordinary Least Squares Estimator of Optimal Adaptive Treatment Strategies.

Biometrical journal. Biometrische Zeitschrift
Estimating optimal adaptive treatment strategies (ATSs) can be done in several ways, including dynamic weighted ordinary least squares (dWOLS). This approach is doubly robust as it requires modeling both the treatment and the response, but only one o...

Diagnostic Performance of ChatGPT-4.0 in Histopathological Analysis of Gliomas: A Single Institution Experience.

Neuropathology : official journal of the Japanese Society of Neuropathology
This study aimed to evaluate the performance of ChatGPT-4.0 as a diagnostic support tool for pathologists in identifying different types of gliomas based on histopathological data and to compare its performance with that of another artificial intelli...

Premolar Ecomorphology in Anthropoid Primates: A Machine Learning Approach.

Journal of morphology
Reconstructing the diets of extinct taxa is essential for understanding their ecologies and evolutionary histories, yet traditional methods and proxies such as molar morphology have limited resolution. The potential of premolar morphology as a dietar...

Paternally Expressed Gene 10 Promoter Methylation Level as a Predictor of HBeAg Seroconversion in Chronic Hepatitis B Patients.

Journal of medical virology
The management of chronic hepatitis B (CHB) encounters challenges like suboptimal antiviral response and the lack of predictive biomarkers. In this study, the role of paternally expressed gene 10 (PEG10) in hepatitis B e antigen (HBeAg) seroconversio...

Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.

Pharmacoepidemiology and drug safety
BACKGROUND: Glucagon-like Peptide-1 Receptor Agonists (GLP1RA) may reduce asthma exacerbation (AE) risk, but it is unclear which populations benefit most. Recent pharmacoepidemiologic studies have employed iterative causal forest (iCF), a machine lea...