AIMC Topic: Hominidae

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Artificial neural networks reconstruct missing perikymata in worn teeth.

Anatomical record (Hoboken, N.J. : 2007) Mar 11, 2024
Dental evolutionary studies in hominins are key to understanding how our ancestors and close fossil relatives grew from the early stages of embryogenesis into adults. In a sense, teeth are like an airplane's 'black box' as they record important varia...
Hominidae Animals Dental Enamel Tooth Wear Tooth Biological Evolution Fossils Humans Neural Networks, Computer
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Fractals and artificial intelligence to decrypt ideography and understand the evolution of language.

The Behavioral and brain sciences Oct 2, 2023
Self-sufficient ideographies are rare because they are stifled by the issue of standardization. Similar issues arise with abstract art or drawings created by young children or great apes. We propose that mathematical indices and artificial intelligen...
Language Animals Child, Preschool Humans Artificial Intelligence Child Hominidae Fractals
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DuDoSS: Deep-learning-based dual-domain sinogram synthesis from sparsely sampled projections of cardiac SPECT.

Medical physics Sep 28, 2022
PURPOSE: Myocardial perfusion imaging (MPI) using single-photon emission-computed tomography (SPECT) is widely applied for the diagnosis of cardiovascular diseases. In clinical practice, the long scanning procedures and acquisition time might induce ...
Image Processing, Computer-Assisted Heart Tomography, Emission-Computed, Single-Photon Tomography, X-Ray Computed Animals Deep Learning Hominidae Humans
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A deep-learning-based workflow to assess taxonomic affinity of hominid teeth with a test on discriminating Pongo and Homo upper molars.

American journal of physical anthropology Apr 16, 2021
OBJECTIVES: Convolutional neural network (CNN) is a state-of-art deep learning (DL) method with superior performance in image classification. Here, a CNN-based workflow is proposed to discriminate hominid teeth. Our hope is that this method could hel...
Deep Learning Workflow Dentin Hominidae Pongo Humans Animals
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A Revised Model of Anatomically Modern Human Expansions Out of Africa through a Machine Learning Approximate Bayesian Computation Approach.

Genes Dec 16, 2020
There is a wide consensus in considering Africa as the birthplace of anatomically modern humans (AMH), but the dispersal pattern and the main routes followed by our ancestors to colonize the world are still matters of debate. It is still an open ques...
Neanderthals Human Migration Hominidae Humans Machine Learning Genetic Variation Genome, Human Racial Groups Asia Biological Evolution History, Ancient Computer Simulation Models, Theoretical Animals Europe Africa Bayes Theorem
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Artificial intelligence provides greater accuracy in the classification of modern and ancient bone surface modifications.

Scientific reports Nov 2, 2020
Bone surface modifications are foundational to the correct identification of hominin butchery traces in the archaeological record. Until present, no analytical technique existed that could provide objectivity, high accuracy, and an estimate of probab...
Tooth Archaeology Fossils Hominidae Africa Europe Bone and Bones Artificial Intelligence Animals Humans
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Predicting lysine-malonylation sites of proteins using sequence and predicted structural features.

Journal of computational chemistry May 14, 2018
Malonylation is a recently discovered post-translational modification (PTM) in which a malonyl group attaches to a lysine (K) amino acid residue of a protein. In this work, a novel machine learning model, SPRINT-Mal, is developed to predict malonylat...
Mice Hominidae Machine Learning Humans Protein Processing, Post-Translational Saccharopolyspora Bacterial Proteins Animals Molecular Structure Lysine Malonates
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Distinguishing butchery cut marks from crocodile bite marks through machine learning methods.

Scientific reports Apr 10, 2018
All models of evolution of human behaviour depend on the correct identification and interpretation of bone surface modifications (BSM) on archaeofaunal assemblages. Crucial evolutionary features, such as the origin of stone tool use, meat-eating, foo...
Fossils Computational Biology Machine Learning Hominidae Alligators and Crocodiles Bone and Bones Animals Tool Use Behavior Bites and Stings Archaeology
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Technical Note: Using Machine Learning to Predict Locomotor Behavior in Great Apes and Humans From Femur Metaphyseal Shape.

American journal of biological anthropology Jun 1, 2025
OBJECTIVES: The morphology of the hominoid distal femoral metaphyseal surface has been demonstrated to reflect locomotor behavior throughout ontogeny. Here, we quantify metaphyseal surface morphology to evaluate its predictive relationship to locomot...
Female Young Adult Adult Humans Locomotion Machine Learning Femur Hominidae Animals Male Imaging, Three-Dimensional
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