AIMC Topic: Humans

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Functional connectivity between non-motor and motor networks predicts motor recovery changes after stroke.

Scientific reports
Stroke impairs limb motor function, which affects patients' quality of life and imposes economic burdens. Early prediction of motor recovery is essential for guiding treatment and rehabilitation. While the corticospinal tract is a known biomarker, th...

An enhanced social emotional recognition model using bidirectional gated recurrent unit and attention mechanism with advanced optimization algorithms.

Scientific reports
Social-emotional learning (SEL) is gradually becoming a region of attention for defining children's school readiness and forecasting academic success. It is the procedure of incorporating cognition, behaviour, and emotion into daily life. School stru...

Intelligent feature fusion with dynamic graph convolutional recurrent network for robust object detection to assist individuals with disabilities in a smart Iot edge-cloud environment.

Scientific reports
Smart Internet of Things (IoT)-edge-cloud computing defines intelligent systems where IoT devices create data at the network's edge, which is then further processed and analyzed in local edge devices before transmission to the cloud for deeper insigh...

Hybrid intelligence in medical image segmentation.

Scientific reports
Medical image segmentation is vital for precise identification and analysis of anatomical structures and pathological regions, yet traditional models often fall short in aligning with clinical workflows, requiring extensive manual correction even whe...

Patent protection of biological genetic resources based on deep learning and artificial intelligence.

Scientific reports
With the rapid development of artificial intelligence (AI), deep learning has provided new ideas for the patent protection of biological genetic resources in the field of intellectual property. This paper aims to explore the application of deep learn...

Development and validation of the risk stratification based on deep learning and radiomics to predict survival of advanced cervical cancer.

Scientific reports
Advanced cervical cancer (aCC) is associated with a poor prognosis. This study aimed to develop and validate a deep learning-based risk stratification model to predict overall survival in aCC patients using pre-treatment CT images. A total of 396 pat...

The BRAINTEASER Datasets: Clinical, Wearable and Environmental Data for ALS & MS Progression Modeling.

Scientific data
Amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) are debilitating diseases with unpredictable progression. Artificial Intelligence-based tools for modelling disease progression could significantly improve the quality of life for patien...

MarkerPredict: predicting clinically relevant predictive biomarkers with machine learning.

NPJ systems biology and applications
Precision oncology relies on predictive biomarkers for selecting targeted cancer therapies. Network-based properties of proteins, together with structural features such as intrinsic disorder, are likely to shape their potential as biomarkers. We ther...

Aetiological clustering of newly diagnosed type 2 diabetes using machine learning: a retrospective cross-sectional study in Dubai, UAE.

BMJ open
OBJECTIVES: Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to val...

Assessing Pharmacists' Use and Perception of AI Chatbots in Pharmacy Practice: Cross-Sectional Survey Study.

JMIR medical education
BACKGROUND: The use of artificial intelligence (AI)-based large language model chatbots such as ChatGPT has become increasingly popular in many disciplines. However, concerns exist regarding ethics, legal considerations, accuracy, and reproducibility...