AIMC Topic: Humans

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Leveraging agent-based models and deep reinforcement learning to predict taxis in cell migration.

NPJ systems biology and applications
We present a novel computational framework that combines Agent-Based Modeling (ABM) with Reinforcement Learning (RL) using the Double Deep Q-Network (DDQN) algorithm to determine cellular behavior in response to environmental signals. With this appro...

Optimized AI-based neural decoding from BOLD fMRI signal for analyzing visual and semantic ROIs in the human visual system.

Journal of neural engineering
. AI-based neural decoding reconstructs visual perception by leveraging generative models to map brain activity measured through functional magnetic resonance imaging (fMRI) into the observed visual stimulus.. Traditionally, ridge linear models trans...

Chatbot-Based Version of a World Health Organization-Validated Intervention for Stress Management in Patients With Breast Cancer (Self-Help Plus): Protocol for a Pilot Feasibility Study.

JMIR research protocols
BACKGROUND: Emerging digital tools play an innovative and key role in supporting women's psychological well-being throughout the different stages and challenges of cancer. The development and adoption of digital interventions, including chatbots and ...

Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT.

Stroke and vascular neurology
BACKGROUND: CT is commonly used to image patients with ischaemic stroke but radiologist interpretation may be delayed. Machine learning techniques can provide rapid automated CT assessment but are usually developed from annotated images which necessa...

Strokeformer: A novel deep learning paradigm training transformer-based architecture for stroke prognosis prediction.

PloS one
Stroke, a common neurological disorder, is considered one of the leading causes of death and disability worldwide. Stroke prognosis issues involve using clinical characteristics collected from patients presented in tabular form to determine whether t...

Identification of core genes in the extracellular matrix and the regulatory mechanisms of the immune microenvironment in idiopathic pulmonary fibrosis using WGCNA and machine learning methods.

PloS one
OBJECTIVE: This research aims to detect genes associated with the extracellular matrix (ECM) in idiopathic pulmonary fibrosis (IPF) using bioinformatics techniques and investigate their relationships with immune infiltration, with the goal of identif...

Revealing potential interfering genes between abdominal aortic aneurysm and periodontitis through machine learning and bioinformatics analysis.

PloS one
This study aimed to identify potential interacting genes between abdominal aortic aneurysm (AAA) and periodontitis. To achieve this, we obtained datasets of AAA and periodontitis from the GEO database, conducted differential analysis on the AAA datas...

Enhancing the early detection of Alzheimer's disease using an integrated CNN-LSTM framework: A robust approach for fMRI-based multi-stage classification.

PloS one
Alzheimer's Disease poses a significant challenge as a progressive and irreversible neurological condition striking the elderly population. Its incurable nature correlates with a significant rise in death rates. However, early detection can slow its ...

Overlapping community detection based on bridging structural features and fuzzy C-means.

PloS one
In recent years, research on community structure for complex networks has received increasing greater attention, and the overlapping community structure is more closely related to the actual social structure than the non-overlapping community structu...

Comparative analysis of outcomes in high KDPI spectrum kidney transplants using unsupervised machine learning algorithm.

PloS one
BACKGROUND: The Kidney Donor Profile Index (KDPI) is a continuous metric used to estimate the risk of allograft failure for kidneys from deceased donors. Lower KDPI scores are associated with longer post-transplant kidney function. This study aims to...