AIMC Topic: Humans

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Stock price dynamics prediction based on multi-scale fractals and deep learning.

PloS one
The complexity of stock price fluctuations stems from its multi-scale characteristics, nonlinear dynamic characteristics, and fractal structure. To better capture the fractal characteristics of stock prices, this paper creatively proposes a predictio...

ceRNA regulatory network and immune-neurodegenerative mechanisms of peripheral CD4+ T cells in parkinson's disease.

PloS one
Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss and neuroinflammation, with emerging roles of peripheral immune dysregulation in disease progression. This study aimed to investigate the regulatory ne...

From data to diagnosis: An innovative approach to epilepsy prediction with CGTNet incorporating spatio-temporal features.

PloS one
Epilepsy affects around 50 million people globally, causing significant burdens. While many methods predict seizures, current models struggle with handling spatiotemporal features and balancing accuracy with computational efficiency.This paper introd...

Integrating graph neural networks and LSTM for path optimization in smart port multi-modal systems.

PloS one
This paper addresses the challenges of dynamic environments and multimodal data fusion in multimodal transport path optimization for smart ports by proposing a GL-SSL Model that integrates Graph Neural Networks (GCN), Long Short-Term Memory (LSTM), a...

The Omics Molecule Extractor: A Web Application for the Selection of Potential Biomarker Panels.

Journal of proteome research
Selecting molecular panels that are applicable to classify the health state of patients is a common task in omics data analysis. Existing software for molecule selection lacks features to select molecule panels from large data sets, requires programm...

Twelve tips for developing and implementing AI curriculum for undergraduate medical education.

Medical education online
The rapid evolution of artificial intelligence (AI) and its growing role in clinical settings have made AI education a priority in undergraduate medical education. To support this, AI curricula must align with existing medical education frameworks wh...

Medical students' perceptions of AI-based feedback and feedforward on communication skills in doctor-patient consultation - an acceptance study in a video-based simulation.

Medical education online
Feedback and feedforward are highly relevant in promoting students' learning. With advances in artificial intelligence (AI), new opportunities to support feedback and feedforward are emerging. However, few studies have explored how medical students p...

Deep Learning vs Classical Methods in Potency and ADME Prediction: Insights from a Computational Blind Challenge.

Journal of chemical information and modeling
Reliable prediction of compound potency and the ADME profile is crucial in drug discovery. With the recent surge of AI and deep learning frameworks, it remains unclear whether these modern techniques offer statistically significant improvement over t...

Machine Learning Accelerates Discovery of High-Performance Corrole Photosensitizers for Optical Imaging Diagnosis and Photodynamic Therapeutics of Nasopharyngeal Carcinoma.

The journal of physical chemistry letters
This study centers on corrole, an emerging photosensitizer with great application potential, and innovatively develops an intelligent machine learning-based screening strategy. Through integrating molecular descriptor generation, feature engineering,...

Identification of PIWI-interacting RNAs based models for lung adenocarcinoma early detection: a multicenter cohort study.

Molecular biomedicine
Early detection of lung adenocarcinoma (LUAD) remains a major clinical challenge despite the widespread application of low-dose computed tomography (LDCT). Circulating PIWI-interacting RNAs (piRNAs), characterized by tumor-specific expression and hig...