AIMC Topic: Humans

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GR-AttNet: Robotic grasping with lightweight spatial attention mechanism.

PloS one
Robotic grasping is crucial in manufacturing, logistics, and service robotics, but existing methods struggle with object occlusion and complex arrangements in cluttered scenes. We propose the Generative Residual Attention Network (GR-AttNet), based o...

Identification and validation of palmitoylation-related signature genes based on machine learning for prostate cancer.

PloS one
Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men, with challenges in diagnosis and treatment due to tumor heterogeneity. This study identifies palmitoylation-related signature genes as potential diagnostic and therapeu...

Advances in deep reinforcement learning enable better predictions of human behavior in time-continuous tasks.

PloS one
Humans have to respond to everyday tasks with goal-directed actions in complex and time-continuous environments. However, modeling human behavior in such environments has been challenging. Deep Q-networks (DQNs), an application of deep learning used ...

AttentionDriveNet: Fusion of deep cognitive network with Attention modeling for robust navigation in Self-driving vehicles.

PloS one
Self-driving vehicles are envisioned as automated and safety-focused vehicles facilitating smooth movement on roads. This research proposes a novel, robust, and intelligent navigation framework for such vehicles through an integrated fusion of advanc...

Decoding brand sentiments: Leveraging customer reviews for insightful brand perception analysis using natural language processing and Tableau.

PloS one
Traditional survey-based feedback has given way to real-time online reviews, yet transforming this unstructured text into actionable knowledge remains difficult. Focusing on the highly competitive smartphone market, where customer sentiment shapes br...

Temporal shifts in prognostic factors for 90- and 180-day outcomes after stroke thrombolysis: A machine learning analysis.

PloS one
INTRODUCTION: Prognostication at 90 and 180 days after thrombolysis for acute ischemic stroke (AIS) is critical, yet the temporal evolution of key predictors remains inadequately understood. The utility of machine learning for systematically comparin...

Artificial intelligence based personalized student feedback system -Sisu Athwala' to enhance exam performance of medical undergraduates.

PloS one
BACKGROUND: In medical education, mentoring and feedback play crucial roles. Providing feedback on exam performance is a vital component as it allows students to improve. Feedback has to be tailor made and specific to the individual student. This nee...

ProSECFPs: A Novel Fingerprint-Based Protein Representation Method for Missense Mutation Pathogenicity Prediction.

Journal of chemical information and modeling
Developing effective computational representations of protein sequences is crucial for advancing diverse areas of computational biology and bioinformatics. Ideal representations must be computationally efficient, scalable, informative, flexible acros...

Usefulness of Data Simulation for Training Deep Learning Denoising Algorithms in Infrared Spectral Histology.

Analytical chemistry
This study investigates the use of simulated data to train deep learning models for denoising infrared spectral images of paraffin-embedded tissue sections in clinical applications. Noise in Fourier-transform infrared spectroscopy poses significant c...

AI-Assisted Microfluidic Paper-Based Analytical Device with Au-Pt Nanoparticles for Multiplex, Interference-Resistant Quantification of Urinary Biomarkers.

Analytical chemistry
Urinary glucose, creatinine, and uric acid are vital biomarkers for diabetes and kidney disease management. However, multiplex point-of-care detection faces challenges due to insufficient sensitivity in complex urine matrices and signal cross-talk fr...