AIMC Topic: Female

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Cox proportional hazards model with Bayesian neural network for survival prediction.

Scientific reports
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks wit...

Deep learning for classifying imaging patterns of interstitial lung disease associated with idiopathic inflammatory myopathies.

Scientific reports
Diagnosing and classifying the imaging patterns of idiopathic inflammatory myopathies-associated interstitial lung disease (IIM-ILD) is a crucial but challenging task requiring specialized physicians' expertise. This study aims to develop and validat...

Development and validation of a diagnostic prediction model for pancreatic ductal adenocarcinoma: VAPOR 1, protocol for a prospective multicentre case-control study.

BMJ open
INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) continues to have extremely poor patient outcomes, unlike other cancer types which have seen significant improvements in their treatments and survival. A major contributing factor is that PDAC is ...

Evaluating the Quality and Understandability of Radiology Report Summaries Generated by ChatGPT: Survey Study.

JMIR formative research
BACKGROUND: Radiology reports convey critical medical information to health care providers and patients. Unfortunately, they are often difficult for patients to comprehend, causing confusion and anxiety, thereby limiting patient engagement in health ...

Misleading Results in Posttraumatic Stress Disorder Predictive Models Using Electronic Health Record Data: Algorithm Validation Study.

Journal of medical Internet research
BACKGROUND: Electronic health record (EHR) data are increasingly used in predictive models of posttraumatic stress disorder (PTSD), but it is unknown how multivariable prediction of an EHR-based diagnosis might differ from prediction of a more rigoro...

A Machine Learning Model for Predicting Sarcopenia Among Middle-Aged Adults: Development and External Validation.

JMIR medical informatics
BACKGROUND: Sarcopenia is a common muscle disorder in older adults, and its early identification and management in middle-aged populations are essential for ensuring a healthier later life. Detecting sarcopenia at an earlier stage may reduce the futu...

MRI-based machine-learning radiomics of the liver to predict liver-related events in hepatitis B virus-associated fibrosis.

European radiology experimental
BACKGROUND: The onset of liver-related events (LREs) in fibrosis indicates a poor prognosis and worsens patients' quality of life, making the prediction and early detection of LREs crucial. The aim of this study was to develop a radiomics model using...

Integration of Multi-omics Data Based on Deep Learning for Subtyping of Low-Grade Glioma.

Journal of molecular neuroscience : MN
Low-grade gliomas (LGGs) represent a complex and aggressive category of brain tumors. Despite recent advancements in molecular subtyping and characterization, the necessity to identify additional molecular subtypes and biomarkers remains. To delineat...

Early embryo development: the current perspective in molecular evaluation and clinical status.

Systems biology in reproductive medicine
Early embryo development and competence mechanisms are paramount to ART's success but are still underexplored in human-relevant animal models. Clinical embryo evaluation remains largely based on subjectively evaluated morphological characteristics. I...

Predicting prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure from longitudinal ultrasound images using a multi-task deep learning approach.

Annals of medicine
BACKGROUND: Individualized risk stratification in hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) remains challenging. This study aimed to develop and validate a multi-task deep learning model using longitudinal liver ultrasound i...