AIMC Topic: Female

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Data-Driven Sustainable Campaigns to Decipher Invasive Breast Cancer Features.

ACS biomaterials science & engineering
The intrinsic complexity of biological processes often hides the role of dynamic microenvironmental cues in the development of pathological states. Microphysiological systems (MPSs) are emerging technological platforms that model dynamics of tissue-...

Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study.

Annals of medicine
BACKGROUND: High intraoperative blood pressure variability (HIBPV) is significantly associated with postoperative adverse complications. However, practical tools to characterize perioperative factors associated with HIBPV remain limited. This study a...

Ultra-early detection of S100B biomarkers using a nanophotonic biosensor with deep learning quantification: A clinical model based on EDAS patients.

Biosensors & bioelectronics
BACKGROUND: Ultra-early detection of brain injury biomarkers within the critical first hour post-injury remains a major clinical challenge in mild traumatic brain injury (mTBI) management. Conventional platforms (e.g., ELISA) suffer from limited sens...

Machine learning approach to DNA methylation and neuroimaging signatures as biomarkers for psychological resilience in young adults.

Behavioural brain research
Psychological resilience is influenced by both psychological and biological factors. However, the potential of using DNA methylation (DNAm) probes and brain imaging variables to predict psychological resilience remains unclear. This study aimed to in...

Familial Differences in Personal PM Exposure within a Rural African Community Explained with Spatiotemporal Exposure Apportionment.

Environmental science & technology
Exposure to fine particulate matter (PM) from solid-fuel combustion is a major determinant of global morbidity and mortality. However, variations in exposure remain uncertain across many high-risk populations. This work describes personal PM exposure...

Development and validation of machine learning-based risk prediction models for ICU-acquired weakness: a prospective cohort study.

European journal of medical research
BACKGROUND: Intensive care unit (ICU)-acquired weakness (ICUAW) is a prevalent complication in critically ill patients, marked by symmetrical respiratory and limb muscle weakness, which adversely affects long-term outcomes. Early identification of hi...

Effects and neural mechanisms of a brain-computer interface-controlled soft robotic glove on upper limb function in patients with subacute stroke: a randomized controlled fNIRS study.

Journal of neuroengineering and rehabilitation
BACKGROUND AND PURPOSE: The brain-computer interface-based soft robotic glove (BCI-SRG) holds promise for upper limb rehabilitation in subacute stroke patients, yet its efficacy and neural mechanisms are unclear. This study aimed to investigate the t...

A multi-omic single-cell landscape reveals transcription and epigenetic regulatory features of t(8;21) AML.

Journal of translational medicine
BACKGROUND: Comprehensive analysis of single-cell transcriptome and chromatin accessibility will contribute to interpret the heterogeneity of acute myeloid leukemia (AML). We hypothesize that integrating single-cell transcriptomic and chromatin acces...

Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients.

BMC medical informatics and decision making
BACKGROUND: Coronary artery disease (CAD) remains a leading cause of global mortality, with stroke constituting a significant complication among patients undergoing coronary revascularization procedures, such as percutaneous coronary intervention (PC...

Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning.

BMC medical informatics and decision making
BACKGROUND: In the Intensive Care Unit (ICU), data stored in patient data management systems (PDMS) is commonly used in clinical practice and research. Parameters from point-of-care arterial blood gas (BG) analysis are used in the diagnosis and defin...