AIMC Topic: Humans

Clear Filters Showing 3451 to 3460 of 95995 articles

Machine learning-assisted detection of single-point mutations DNA-templated gold nanoparticle growth.

Nanoscale
Detecting single point mutations, such as PIK3CA mutations, is vital for precision diagnostics but remains challenging due to subtle sequence differences. This study introduces a machine learning-assisted colorimetric biosensor that utilizes DNA-temp...

Robust emotion recognition for complex environments: ChildEmoNet model based on DETR-ResNet50 cascaded architecture.

PloS one
Emotion recognition faces significant challenges in complex real-world environments, particularly under facial occlusion conditions that severely impact traditional deep learning approaches. This research proposes ChildEmoNet, a novel cascaded emotio...

Identifying determinants of readmission and death post-stroke using explainable machine learning.

PloS one
BACKGROUND: Stroke remains a global health challenge with high rates of mortality and rehospitalization placing significant demands on healthcare systems. Identifying factors that determine outcomes of post-hospitalization improves resource allocatio...

From CBC to clarity: Interpretable detection of beta-thalassemia carriers in imbalanced datasets.

PloS one
Thalassemia is an inherited blood disorder and is among the five most prevalent birth-related complications, especially in Southeast Asia. Thalassemia is classified into two main types-alpha-thalassemia and beta-thalassemia-based on the reduced or ab...

Multi-objective representation learning for road networks and trajectories with spatial-temporal fusion and contrastive signals.

PloS one
Modeling and learning representations for road networks and vehicle trajectories are crucial in enabling intelligent transportation systems, with applications ranging from traffic forecasting to many other downstream inference tasks. However, learnin...

Multi-scale error-driven dense residual network for image super-resolution reconstruction.

PloS one
Image super-resolution reconstructs high-resolution images from low-resolution inputs. However, current single-image super-resolution techniques often struggle to capture multi-scale information and extract high-frequency details, which compromises r...

Flat-Lattice-CNN: A model for Chinese medical-named-entity recognition.

PloS one
BACKGROUND: In the field of internet-based healthcare, the complexity of pathology features across various disciplines, coupled with the lack of medical training among most patients, results in medical named entities in doctor patient dialogue texts e...

Deep reinforcement learning-based multi-lane mixed traffic ramp merging strategy.

PloS one
Due to concentrated conflicts, on-ramp merging is an important scenario in the study of new hybrid traffic control. Current research mainly focuses on optimizing the vehicle passage sequence of ramp vehicles merging with mainline vehicles in single-l...

Revealing and validating the biomarkers associated with demethylation in major depressive disorder: comprehensive insights based on bulk RNA sequencing data, single-nucleus RNA sequencing data, and clinical experiments.

Journal of affective disorders
BACKGROUND: The demethylation is suspected to play a role in the development of major depressive disorder (MDD), but the precise biological mechanisms remain unclear. Therefore, this study aimed to investigate biomarkers linked to demethylation in MD...

PyaiVS unifies AI workflows to accelerate ligand discovery and yields ABCG2 inhibitors.

European journal of medicinal chemistry
Developing optimized AI models for virtual screening requires coordinated selection of algorithms, molecular representations, and data splitting strategies, yet lacks integrated tools. We present PyaiVS, a Python package that integrates nine machine ...