AIMC Topic: Humans

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A lightweight single-view contrastive learning hypergraph neural network for food-microbe-disease association prediction.

BMC bioinformatics
BACKGROUND: Identifying potential associations among food, gut microbiota and disease is fundamental for elucidating interaction mechanisms and advancing personalized healthy dietary strategies. While computational methods have been extensively appli...

Training convolutional neural networks with the Forward-Forward Algorithm.

Scientific reports
Recent successes in image analysis with deep neural networks are achieved almost exclusively with Convolutional Neural Networks (CNNs), typically trained using the backpropagation (BP) algorithm. In a 2022 preprint, Geoffrey Hinton proposed the Forwa...

Empowering people with intellectual disabilities using integrated deep learning architecture driven enhanced text-based emotion classification.

Scientific reports
Emotion recognition is an important research field including psychology, healthcare, and human-computer interaction (HCI). However, conventional techniques mainly rely on textual analysis and facial expressions, and they also have potential flaws, ma...

Morphological alterations of peridroplet mitochondria in human liver biopsy.

Scientific reports
Mitochondrial dysfunction and the accumulation of lipid droplets (LD) contribute to the pathogenesis of liver diseases. Mitochondria bound to LD, termed peridroplet mitochondria (PDM), form a subpopulation with distinct functions compared to cytoplas...

Novel morphological indexes for quantitative evaluation of cerebral aneurysm irregularity.

Scientific reports
A cerebral aneurysm may present irregularities associated with rupture risks. However, conventional morphological parameters are limited in evaluating the aneurysm irregularity. Although the mass moment of inertia has been devised for the irregularit...

Identified endoplasmic reticulum stress-related molecular cluster and immune characterization in endometriosis.

Scientific reports
Endometriosis is a common disease among women of childbearing age, and endoplasmic reticulum stress (ERS), a response involved in regulating protein homeostasis, has been linked to its pathogenesis. To identify ERS-related hub genes, this study seque...

Development and validation of an interpretable machine learning model for early prediction in patients with diabetes and sepsis.

Scientific reports
We aimed to identify and validate key predictive factors influencing 28-day survival rates in patients with diabetes and sepsis and to develop a predictive model based on these factors to assist clinical decision-making. In this retrospective cohort ...

Web based AI-driven framework combining multi-modal data with CNN and LLM for Parkinson's disease diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a wide spectrum of motor and non-motor symptoms, often leading to delayed or inaccurate diagnosis. Conventional diagnostic methods frequently suffer from limited se...

Leveraging fundus images for on device eye disease diagnosis with AI powered lightweight software hardware framework.

Scientific reports
Vision loss due to illness can result from various medical conditions that affect the eyes. Advanced devices like OCT and ultra-widefield retinal cameras are expensive, making them less accessible in resource-limited settings. While eye image capture...

Label-free estimation of regulatory T cell activation markers using Raman spectroscopy with machine learning.

Scientific reports
Regulatory T cells are a class of T lymphocytes which respond to activation signals by expanding their cell numbers, and whose culturing and expansion are of significant clinical interest. Cellular activation states are used to inform process control...