AIMC Topic: Humans

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An overview of gene and cell therapy approaches for Alzheimer's disease.

Metabolic brain disease
Alzheimer's disease (AD), acknowledged as the leading cause of dementia, is defined by the accumulation of amyloid plaques and neurofibrillary tangles (NFTs) in the brain. This condition presents a significant challenge to global health due to its co...

An Innovative Method for Refractory Epilepsy Diagnosis Based on Microstate Analysis and Graph Convolutional Network.

Journal of medical systems
This study systematically investigates the alterations in electroencephalogram (EEG) microstates in patients with refractory epilepsy(RE) across different seizure stages. A novel EEG microstate analysis framework is proposed to address the limitation...

Development and Validation of an Interpretable Hemodynamics-Based Machine Learning Model for Predicting Cerebral Arteriovenous Malformation Rupture.

Translational stroke research
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...

Enhanced machine learning and hybrid ensemble approaches for Coronary Heart Disease prediction.

PloS one
Coronary heart disease (CHD) remains the leading cause of mortality worldwide, disproportionately affecting low- and middle-income countries where diagnostic resources are limited. Traditional statistical models often fail to deliver adequate predict...

Intelligent glucose management in hospitalized patients: Short-term glucose and adverse events prediction.

PloS one
The management of blood glucose in hospitalized patients is confined to retrospective interventions, preventing healthcare professionals from predicting patients' blood glucose levels and potential adverse events in advance. This study employs a deep...

Machine learning-based prediction of glioma grading.

PloS one
OBJECTIVE: Gliomas are among the most common and heterogeneous primary tumours of the central nervous system. Accurate grading is essential for treatment planning and prognosis, yet conventional histopathological approaches are limited by subjectivit...

Subtype classification of gastric spindle cell tumors in whole slide images.

Computers in biology and medicine
AIMS: Accurate cancer subtype classification is critical due to variations in tumor progression and prognosis. Traditionally, pathologists classified subtypes manually by examining pathological slides under the microscope. To address increasing workl...

Data-Driven Machine Learning Framework for the Regulation of Protein Adsorption on Surfaces.

Langmuir : the ACS journal of surfaces and colloids
Protein adsorption on surfaces is a highly complex process, governed by intricate interactions between protein, surface and surrounding environment. However, accurately predicting protein adsorption amounts and precisely controlling adsorption behavi...

High Na-Adducted Ion Selectivity in Laser Desorption/Ionization Mass Spectrometry with a Steric-Tuned COF.

Analytical chemistry
Laser desorption-ionization mass spectrometry (LDI-MS) is prized for its rapidity, simplicity, low sample consumption, and high throughput in metabolic analysis, with great potential as a diagnostic tool. Herein, an LDI-MS method with sulfone-contain...