AIMC Topic: Datasets as Topic

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Hyperparameter selection for dataset-constrained semantic segmentation: Practical machine learning optimization.

Journal of applied clinical medical physics Oct 10, 2024
PURPOSE/AIM: This paper provides a pedagogical example for systematic machine learning optimization in small dataset image segmentation, emphasizing hyperparameter selections. A simple process is presented for medical physicists to examine hyperparam...
Humans Machine Learning Algorithms Semantics Tomography, X-Ray Computed Image Processing, Computer-Assisted Datasets as Topic
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Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Oct 9, 2024
Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversi...
Animals Gene Expression Profiling Prefrontal Cortex Mice Humans Datasets as Topic Epithelial-Mesenchymal Transition Cell Communication Breast Neoplasms Graph Neural Networks
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Developing and Validating a Multimodal Dataset for Neonatal Pain Assessment to Improve AI Algorithms With Clinical Data.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses Oct 2, 2024
BACKGROUND: Using Artificial Intelligence (AI) for neonatal pain assessment has great potential, but its effectiveness depends on accurate data labeling. Therefore, precise and reliable neonatal pain datasets are essential for managing neonatal pain.
Artificial Intelligence Humans Infant, Newborn Pain Measurement Algorithms Female Reproducibility of Results Pain Male Datasets as Topic
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Feature-based detection of breast cancer using convolutional neural network and feature engineering.

Scientific reports Sep 27, 2024
Breast cancer (BC) is a prominent cause of female mortality on a global scale. Recently, there has been growing interest in utilizing blood and tissue-based biomarkers to detect and diagnose BC, as this method offers a non-invasive approach. To impro...
Datasets as Topic Female Humans Data Analysis Data Display Machine Learning Breast Neoplasms Biomarkers Convolutional Neural Networks Computer Simulation
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Joint inference of discrete cell types and continuous type-specific variability in single-cell datasets with MMIDAS.

Nature computational science Sep 23, 2024
Reproducible definition and identification of cell types is essential to enable investigations into their biological function and to understand their relevance in the context of development, disease and evolution. Current approaches model variability...
Cluster Analysis Humans Datasets as Topic Animals Neural Networks, Computer Single-Cell Analysis Algorithms Computational Biology Brain
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DentAge: Deep learning for automated age prediction using panoramic dental X-ray images.

Journal of forensic sciences Sep 18, 2024
Age estimation plays a crucial role in various fields, including forensic science and anthropology. This study aims to develop and validate DentAge, a deep-learning model for automated age prediction using panoramic dental X-ray images. DentAge was t...
Young Adult Adult Male Middle Aged Deep Learning Adolescent Female Aged Forensic Dentistry Aged, 80 and over Datasets as Topic Humans Child, Preschool Age Determination by Teeth Child Radiography, Panoramic
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Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.

Progress in orthodontics Sep 16, 2024
OBJECTIVES: This study aimed to assess the accuracy of machine learning (ML) models with feature selection technique in classifying cervical vertebral maturation stages (CVMS). Consensus-based datasets were used for models training and evaluation for...
Cephalometry Cervical Vertebrae Datasets as Topic Observer Variation Age Determination by Skeleton Adolescent Child Support Vector Machine Humans Machine Learning Female Male
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Main challenges on the curation of large scale datasets for pancreas segmentation using deep learning in multi-phase CT scans: Focus on cardinality, manual refinement, and annotation quality.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 13, 2024
Accurate segmentation of the pancreas in computed tomography (CT) holds paramount importance in diagnostics, surgical planning, and interventions. Recent studies have proposed supervised deep-learning models for segmentation, but their efficacy relie...
Humans Tomography, X-Ray Computed Deep Learning Datasets as Topic Pancreas
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Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning.

Communications biology Sep 10, 2024
The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-...
Cluster Analysis Neurodegenerative Diseases Supervised Machine Learning Animals Deep Learning Single-Cell Gene Expression Analysis Datasets as Topic Central Nervous System Atlases as Topic Humans
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DepressionEmo: A novel dataset for multilabel classification of depression emotions.

Journal of affective disorders Aug 28, 2024
Emotions are integral to human social interactions, with diverse responses elicited by various situational contexts. Particularly, the prevalence of negative emotional states has been correlated with negative outcomes for mental health, necessitating...
Datasets as Topic Deep Learning Humans Depression Machine Learning Emotions Reproducibility of Results
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