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Integrating anoikis and ErbB signaling insights with machine learning and single-cell analysis for predicting prognosis and immune-targeted therapy outcomes in hepatocellular carcinoma.

Frontiers in immunology
BACKGROUND: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but thei...

Machine learning-based risk prediction for major adverse cardiovascular events in a Brazilian hospital: Development, external validation, and interpretability.

PloS one
BACKGROUND: Studies of cardiovascular disease risk prediction by machine learning algorithms often do not assess their ability to generalize to other populations and few of them include an analysis of the interpretability of individual predictions. T...

Comparative study of machine learning approaches integrated with genetic algorithm for IVF success prediction.

PloS one
INTRODUCTION: IVF is a widely-used assisted reproductive technology with a consistent success rate of around 30%, and improving this rate is crucial due to emotional, financial, and health-related implications for infertile couples. This study aimed ...

A Systematic Review and Meta-Analysis of the Association between Childhood Exposure to Intimate Partner Violence and Intimate Partner Violence Victimization/Perpetration in Adulthood in Africa.

Trauma, violence & abuse
Intimate partner violence (IPV) is widespread in many African countries. Evidence, mainly from Western countries, shows that exposure to IPV in childhood is an important risk factor for experiences of IPV in adulthood. However, to date, no systematic...

Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.

Journal of imaging informatics in medicine
The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and speci...

Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.

Journal of computer assisted tomography
OBJECTIVE: The aim of this study was to assess the effectiveness of a deep learning-based image contrast-boosting algorithm by enhancing the image quality of low-dose computed tomography pulmonary angiography at reduced iodine load.

The first AI-based Chatbot to promote HIV self-management: A mixed methods usability study.

HIV medicine
BACKGROUND: We developed MARVIN, an artificial intelligence (AI)-based chatbot that provides 24/7 expert-validated information on self-management-related topics for people with HIV. This study assessed (1) the feasibility of using MARVIN, (2) its usa...

Artificial Intelligence Improves Prediction of Major Adverse Cardiovascular Events in Patients Undergoing Transcatheter Aortic Valve Replacement Planning CT.

Academic radiology
RATIONALE AND OBJECTIVES: Coronary CT angiography (CCTA) is mandatory before transcatheter aortic valve replacement (TAVR). Our objective was to evaluate the efficacy of artificial intelligence (AI)-powered software in automatically analyzing cardiac...

Machine Learning Model for Predicting Risk Factors of Prolonged Length of Hospital Stay in Patients with Aortic Dissection: a Retrospective Clinical Study.

Journal of cardiovascular translational research
The length of hospital stay (LOS) is crucial for assessing medical service quality. This study aimed to develop machine learning models for predicting risk factors of prolonged LOS in patients with aortic dissection (AD). The data of 516 AD patients ...