AIMC Topic: Humans

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Developing a Community-Specific Daily Weather Health Risk Index Across Australia Using Explainable Machine Learning.

Environmental science & technology
Weather conditions are closely related to human health, yet effective methods for communicating the joint health risks associated with weather-related factors remain limited, especially when accounting for the complex interactions among weather expos...

Silver-Programmed Dual-Optical Au Nanostructures and Machine Learning for Intelligent Biosensing.

Analytical chemistry
The evolution of biosensors demands synergistic improvements in signal transduction and data processing. We present a universal biosensing platform that combines dual-mode signal responses from silver-modulated gold nanorods (AuNRs) and gold-silver n...

Electromechanically induced membrane restructuring enables learning and memory.

Proceedings of the National Academy of Sciences of the United States of America
Human neural networks of interconnected neurons have evolved to be remarkably efficient and are capable of learning and memory through the brain's synaptic plasticity, including short-term plasticity (STP), and long-term potentiation (LTP) and depres...

Development of a diagnostic model for ovarian cancer based on machine learning algorithms and functional analysis of key biomarker SOX17.

Journal of ovarian research
BACKGROUND: Ovarian cancer (OC) demonstrates the poorest prognosis among gynecological malignancies, with five-year survival rates below 45%, primarily due to late-stage diagnosis. To address this challenge, we systematically identified OC-specific d...

Identification of key genes and regulatory networks associated with atherosclerotic carotid artery stenosis through comprehensive bioinformatics analysis and machine learning.

European journal of medical research
OBJECTIVE: To identify the potential diagnostic biomarkers and therapeutic targets of atherosclerotic carotid artery stenosis (ACAS), a comprehensive bioinformatics analysis was conducted to identify its related key genes and regulatory networks.

Differentiation of light chain cardiac amyloidosis and hypertrophic cardiomyopathy by ensemble machine learning-based radiomic analysis of cardiac magnetic resonance.

Orphanet journal of rare diseases
BACKGROUND: We aim to assess the diagnosis performance of an ensemble machine learning (ML) based radiomic analysis of multiparametric cardiac magnetic resonance (CMR) to differentiate light chain cardiac amyloidosis (AL-CA) and hypertrophic cardiomy...

Optimizing myocardial infarction detection: a hybrid CNN-GRU deep learning approach.

BMC medical informatics and decision making
BACKGROUND: Myocardial infarction (MI) is a life-threatening condition caused by sudden interruption of blood supply to the heart. Electrocardiogram (ECG) is the primary tool for MI diagnosis, but interpretation challenges exist. This study aimed to ...

CT radiomics-based explainable machine learning model for accurate differentiation of malignant and benign endometrial tumors: a two-center study.

Biomedical engineering online
OBJECTIVES: This study aimed to develop and validate a CT radiomics-based explainable machine learning model for precise diagnosing of malignancy and benignity specifically in endometrial cancer (EC) patients.

Multi-modal single-cell platform for nanoparticle-enhanced time-series metabolic profiles of CD8 T cell exhaustion in tumor immunosurveillance.

Journal of nanobiotechnology
Cytotoxic T cells (CD8) play a pivotal role in immunosurveillance by identifying and eliminating tumor cells. However, the onset of CD8 T cell exhaustion, characterized by overexpression of immune checkpoint receptors, impairs their function, allowin...

Development and validation of a multidimensional and interpretable artificial intelligence model to predict gout recurrence in hospitalised patients: a real-world, ambispective multicentre cohort study in China.

BMC medicine
BACKGROUND: Gout is the most common inflammatory arthritis. Recurrent flares are common among hospitalised patients and contribute to substantial clinical and economic burden. However, the accurate prediction of inpatient recurrence remains challengi...