AIMC Topic: Female

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Leveraging deep learning to discover interpretable cellular spatial biomarkers for prognostic predictions based on hepatocellular carcinoma histology.

The journal of pathology. Clinical research
The spatial structure of various cell types in the tumour microenvironment (TME) can provide valuable insights into disease progression. However, identifying the spatial organization of diverse cell types that significantly correlates with patient pr...

Incorporating end-user perspectives into the development of a machine learning algorithm for first time perinatal depression prediction.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental health conditions. These algorithms are often developed without considering the perspectives of the affected populations. This study describes the process ...

Liver Fat Fraction and Machine Learning Improve Steatohepatitis Diagnosis in Liver Transplant Patients.

NMR in biomedicine
Machine learning identifies liver fat fraction (FF) measured by H MR spectroscopy, insulinemia, and elastography as robust, non-invasive biomarkers for diagnosing steatohepatitis in liver transplant patients, validated through decision tree analysis....

Volumetric and Diffusion Tensor Imaging Abnormalities Are Associated With Behavioral Changes Post-Concussion in a Youth Pig Model of Mild Traumatic Brain Injury.

NMR in biomedicine
Mild traumatic brain injury (mTBI) caused by sports-related incidents in children and youth often leads to prolonged cognitive impairments but remains difficult to diagnose. In order to identify clinically relevant imaging and behavioral biomarkers a...

Clinical Decision Support for Septic Shock in the Emergency Department: A Cluster Randomized Trial.

Pediatrics
BACKGROUND AND OBJECTIVES: Delays in septic shock diagnosis cause preventable mortality in children. Evidence is limited around early recognition strategies. The hypothesis was that clinical decision support (CDS) based on machine-learning predictive...

Prenatal exposure to criteria air pollution and traffic-related air toxics and risk of autism spectrum disorder: A population-based cohort study of California births (1990-2018).

Environment international
BACKGROUND: Autism spectrum disorder (ASD) prevalence has risen steadily in California (CA) over several decades, with environmental factors like air pollution (AP) increasingly implicated. This study investigates associations between prenatal exposu...

Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND: Steatotic liver disease (SLD) is the most common liver disease worldwide, affecting 30% of the global population. It is strongly associated with the interplay of genetic and lifestyle-related risk factors. The genetic variant accounting f...

Divergence in the sow vaginal microbiota is associated with fertility.

Reproduction (Cambridge, England)
IN BRIEF: Vaginal microbiota composition influences female fertility, however it has not been studied for measuring fertility level in female pigs. This study reveals significant vaginal microbiota composition differences between high reproductive pe...

Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.

Computers in biology and medicine
In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately predicting and early response to lymphoma treatment will be useful for initiating treatment plans to achieve a greater rate of cure or reduced risk of tre...

Time-series deep learning and conformal prediction for improved sepsis diagnosis in primarily Non-ICU hospitalized patients.

Computers in biology and medicine
PURPOSE: Sepsis, a life-threatening condition from an uncontrolled immune response to infection, is a leading cause of in-hospital mortality. Early detection is crucial, yet traditional diagnostic methods, like SIRS and SOFA, often fail to identify s...