Age Estimation Research Articles

BS-clock, advancing epigenetic age prediction with high-resolution DNA methylation bisulfite sequencing data.

DNA methylation patterns provide precise and accurate estimates of biological age due to their robustness and predictable changes associated with aging processes. Although several methylation aging clocks have been developed in recent years, they are primarily designed for DNA methylation array data, which has limited CpG coverage and detection sensitivity compared to bisulfite sequencing data. Here, we present BS-clock, a novel DNA methylation clock for human aging based on bisulfite sequencing data. Using BS-seq data from 529 samples retrieved from four tissues, our BS-clock achieves higher correlations with chronological age in multiple tissue types compared to existing array-based clocks. Our study revealed age-dependent aging rates across different age stages and disease conditions, and overall low cross-tissue prediction capability by applying the model trained on one tissue type to others. In summary, BS-clock overcomes limitations of array-based techniques, offering genome-wide CpG site coverage and more robust and accurate aging quantification. This research paves the way for advanced epigenetic studies of aging and holds promise for developing targeted interventions to promote healthy aging. All analysis codes for reproducing the results of the study are publicly available at https://github.com/hucongcong97/BS-clock. Supplementary data are available at Bioinformatics online.

Archaeology on the edge: radiocarbon chronologies for Aboriginal cliff-top sites of the Murray River, South Australia

Abstract This paper presents new radiocarbon dates for two Aboriginal archaeological complexes situated on the cliff-lines of the Murray River in South Australia (SA); at Pooginook Flat and Tanamee. These dates represent the first age estimates for archaeological sites within the Upper Gorge section of the Murray River. The dates ranged from ca. 11 cal ka to the Late Holocene. The research supports previous evidence which has indicated that sites located along the Murray cliffs preserve much of the oldest evidence of Aboriginal peopling along the Murray River corridor in SA. The new dates also allow us to contribute to discussions concerning broader chronological trends in Aboriginal lifeways within the Murray-Darling Basin (MDB). Specifically, the new ages add some insight into the nature and timing of early Aboriginal occupation along the Murray River corridor in SA and further evidence that the LGM acted as a significant inhibitive factor for intensive occupation of this riverscape. The conservation of these significant and informative cliff-top sites remains precarious, however, and there is an imperative to continue to record and sample the extant sites.

A critical comparative study of the performance of three AI-assisted programs for bone age determination.

To date, AI-supported programs for bone age (BA) determination for medical use in Europe have almost only been validated separately, according to Greulich and Pyle (G&P). Therefore, the current study aimed to compare the performance of three programs, namely BoneXpert, PANDA, and BoneView, on a single Central European population. For this retrospective study, hand radiographs of 306 children aged 1-18 years, stratified by gender and age, were included. A subgroup consisting of the age group accounting for 90% of examinations in clinical practice was formed. The G&P BA was estimated by three human experts-as ground truth-and three AI-supported programs. The mean absolute deviation, the root mean squared error (RMSE), and dropouts by the AI were calculated. The correlation between all programs and the ground truth was prominent (R2 ≥ 0.98). In the total group, BoneXpert had a lower RMSE than BoneView and PANDA (0.62 vs. 0.65 and 0.75 years) with a dropout rate of 2.3%, 20.3% and 0%, respectively. In the subgroup, there was less difference in RMSE (0.66 vs. 0.68 and 0.65 years, max. 4% dropouts). The standard deviation between the AI readers was lower than that between the human readers (0.54 vs. 0.62 years, p < 0.01). All three AI programs predict BA after G&P in the main age range with similar high reliability. Differences arise at the boundaries of childhood. Question There is a lack of comparative, independent validation for artificial intelligence-based bone age estimation in children. Findings Three commercially available programs estimate bone age after Greulich and Pyle with similarly high reliability in a central European cohort. Clinical relevance The comparative study will help the reader choose a software for bone age estimation approved for the European market depending on the targeted age group and economic considerations.

Neoproterozoic volcanosedimentary and plutonic complexes of Northern Ulutau (Central Kazakhstan)

The article presents the results of studying and substantiating the age of Late Precambrian volcanogenic sedimentary and plutonic complexes of the northern part of the Ulutau terrane (Northern Ulutau) in the west of Central Kazakhstan. The age estimates obtained (SHRIMP II, ID-TIMS, LA-ICP-MS) indicate the formation of acidic effusions and granitoids in the second half of the Tonian Neoproterozoic period ~835‒747 million years ago. Geochronological and isotope-geochemical data allow us to consider these formations as analogues of stratified and plutonic complexes of Southern Ulutau, formed in various parts of the lateral series of structures of the late precambrian active continental margin.

Computed tomography study of cranial vault thickness in Malaysian subadult population.

Cranial vault thickness (CVT) and its variations provide valuable insights into an individual's biological attributes such as age and sex. This paper aimed to assess the correlations of CVT with age and sex and develop a regression model for age estimation in Malaysian subadults using computed tomography (CT) images. A total of 521 CT images (male/female: 279/242; age range: 0-20 years; Malay/Chinese/Indian: 221/145/155) were included in the study. Correlations of CVT measurements with age and sex, including frontal bone thickness (FBT), occipital bone thickness (OBT), left parietal bone thickness (LPBT), and right parietal bone thickness (RPBT) were assessed and regression formulae were developed for age estimation in subadults. A significant correlation between CVT measurements and age was demonstrated (p < 0.001). Age estimation was most accurate in the younger age group (< 2 years) at frontal and occipital, and accuracy decreases in the older age groups. Additionally, sexual dimorphism was evident in the frontal and parietal bone thickness within the age range of 3-6 years and 16-20 years, respectively. In conclusion, the findings suggested CVT measurements could be used to corroborate other age estimation methods for subadults.

Forensic age estimation in adults based on multidetector computed tomography analysis of bone density in the medial meta-epiphyseal region of clavicle.

The aim of this study was to investigate the potential of using multidetector computed tomography (MDCT) to measure the bone mineral density (BMD) in the medial meta-epiphyseal region of clavicle (MERC) for adult age estimation. A total of 1064 chest MDCT scans from individuals aged 21 to 102years were utilized to determine the MERC BMD. The Mimics software was used for the BMD measurements, and the average BMD of both MERC was also calculated. Regression analysis was conducted with chronological age as a dependent variable and MERC BMD as an independent variable to establish a mathematical model for age estimation. The mean absolute error (MAE) was calculated to evaluate the accuracy of the regression model using an independent validation sample. Among all the models, the cubic regression model showed the highest correlation between MERC BMD and chronological age and also provided the most accurate age prediction for both males and females (MAE = 9.41 for males, MAE = 10.38 for females). Our study suggests that BMD measured by MERC can be utilized for age estimation in adults when more reliable indicators are not available.

Exploring optimal methods for age-at-death estimation using pulp/tooth area ratios: a South African study.

Age-at-death estimation is pivotal in the identification of unknown human decedents in forensic medicine. The pulp/tooth area ratio (PAR) method, assessing pulp cavity size as a marker of secondary dentine apposition, is widely utilised for adult age estimation. Despite extensive evaluation of this technique, the influence of image type and enamel area inclusion on method accuracy is insufficiently explored. The present study evaluated the PAR method's applicability using maxillary canines from a South African cadaveric sample, examining reliability, sex bias, and accuracy across different image types and enamel area considerations. An observational, cross-sectional study design was followed. Fifty-two adult maxillary canines were radiographed, sectioned, and analysed using stereomicroscopy. Labiolingual and mesiodistal periapical radiographs, alongside labiolingual stereomicroscopic tooth section images, were analysed using ImageJ to calculate PARs. Age estimation linear regression models were developed for each image type, with and without enamel area inclusion. Models were compared for performance and accuracy using best-subsets regression and cross-validation analyses. Results indicated that the PAR method is a reliable, sex-independent technique, providing relatively accurate age-at-death estimates for South African adults. Image type significantly influenced accuracy, with tooth section images exhibiting the best/lowest error values, followed by labiolingual and mesiodistal radiographs, respectively. Exclusion of enamel area consistently enhanced model performance across all image types. This study contributes valuable data to the underexplored field of dental age estimation techniques for South African adults, highlighting optimal approaches when applying the PAR method to maxillary canines. Additionally, it introduces a refined stereomicroscopic technique, augmenting and enhancing existing practices.

Evaluation of two scoring systems assessing the epiphyseal union at shoulder joint as predictors of chronological age among a sample of Egyptians.

Age estimation has extensive medicolegal implications in civil and criminal identification. Despite the surge in adopting radiological investigations to assess developmental bony changes, the shoulder joint is understudied. A cross-sectional study was conducted, enrolling 283 shoulder radiographs of Egyptians, investigating the reliability of two previously established scores as predictors of chronological age using the epiphyseal maturation of proximal humerus and acromion process. Epiphyseal union of proximal humerus commenced at age of 16.1-17 and completed around 21, while complete acromial union was observed around the age of 20.8. Females significantly preceded males and showed lower mean total Scores A and B at different maturation stages. There was a significant strong positive correlation between the chronological age and the epiphyseal maturation of humerus, acromion and total shoulder scores with correlation coefficients between 0.84 and 0.9. The receiver operating characteristic curves showed significant discriminating power of the total shoulder Scores A and B as predictors of the ages of 14 and 16, with area under curves above 0.9, minimal accuracy of 96.5% and p values of 0.001. Six proposed models were established where the model "age=0.318+(0.388) total shoulder Score A+(2.842) total shoulder Score B+1.931 (sex)" showed the best significant prediction power of radiographic evaluation of epiphyseal maturation in the proximal humerus and acromion in estimating the ages between 8 and around 20years (R2 of 0.812). Applying this model to assess the chronological age, especially if the results from the hand and teeth are inconclusive, is promising.

Noninvasive, epigenetic age estimation in an elasmobranch, the cownose ray (Rhinoptera bonasus)

Age data are essential for estimating life history parameters and are thus critical for population assessment, management, and conservation. Traditional vertebrae-based age estimation in elasmobranchs can be costly, time intensive, of low accuracy, and is by necessity lethal. Herein, epigenetic clocks were developed for an elasmobranch, the cownose ray (Rhinoptera bonasus), using aquarium-born individuals (n = 42) with known dates of birth (age range: 7−7,878 days or 0−21 years) and two tissue types (fin clips and whole blood) that can be sampled in a relatively non-invasive manner. Enzymatically-converted restriction site-associated DNA sequencing (ECrad-seq) was used to identify CpG sites that exhibited age-correlated DNA methylation. The epigenetic clocks developed were highly accurate (mean absolute error, MAE, < 0.75 years) and precise (R2 > 0.98). Age-associated CpG sites were identified across tissues, and a multi-tissue clock was also highly accurate (MAE < 1 year) and precise (R2 = 0.97). Using the developed fin clip clock, three wild-caught individuals of unknown age but managed in aquariums for > 22 years were predicted to be 22.10−23.49 years old. Overall, the results have important implications for future epigenetic clock development and noninvasive age estimation in elasmobranchs.

Age estimation on post-mortem CT based on pelvic bone mineral density measurement and the state of putrefaction: a multivariate method.

Age-at-death estimation is an important issue in forensic medicine and anthropology. Initially, methods relied on morphological criteria, but with the advancement of radiology, new techniques such as morphological studies on multi-slice computed tomography (CT) reconstructions have emerged. Recent studies have shown promising results by investigating the correlation between age and bone mineral density (BMD). However, there is currently a lack of data on post-mortem CTs (PMCT) involving decomposed bodies, and limited information exists regarding changes in Hounsfield Units measurement in a post-mortem context. In light of these gaps, our study aimed to examine the relationship between age at death and pubic and ilium BMD using a sample of forensic bodies. We also aimed to determine whether post-mortem processes, such as putrefaction, could interfere with this correlation. Our retrospective analysis encompassed 637 PMCTs conducted before medicolegal autopsies at Tours University Hospital. Utilizing simple and multiple linear regressions, we investigated the correlation between age and pubic and ilium BMD, as well as the relationship between BMD and the radiologic alteration index (RAI), a scale employed to quantify the degree of putrefaction. Our findings indicate promising outcomes in age-at-death estimation using pubic and/or ilium BMD for bodies exhibiting no or moderate decomposition (RAI < 80), particularly among individuals under 40years old. However, for highly decomposed corpses (RAI ≥ 80), the presence of gas infiltration significantly influences the BMD of both the ilium and pubis. Consequently, we advocate for the incorporation of the RAI score into the age estimation equation to enhance the accuracy of our results in such cases. Further investigation involving a larger cohort of decomposed bodies could facilitate refinement and validation of our method within this specific population.

Estimates of (convective core) masses, radii, and relative ages for ∼14 000 Gaia-discovered gravity-mode pulsators monitored by TESS

Context. Gravito-inertial asteroseismology saw its birth from the 4-year-long light curves of rotating main-sequence stars assembled by the Kepler space telescope. High-precision measurements of internal rotation and mixing are available for about 600 stars of intermediate mass so far that are used to challenge the state-of-the-art stellar structure and evolution models. Aims. Our aim is to prepare for future large ensemble modelling of gravity-mode pulsators by relying on a new sample of such stars recently discovered from the third Data Release of the Gaia space mission and confirmed by space photometry from the TESS mission. This sample of potential asteroseismic targets is about 23 times larger than the Kepler sample. Methods. We use the effective temperature and luminosity inferred from Gaia to deduce evolutionary masses, convective core masses, radii, and ages for ∼14 000 gravity-mode pulsators classified as such from their nominal TESS light curves. We do so by constructing two dedicated grids of evolutionary models for rotating stars with input physics from the asteroseismic calibrations of Keplerγ Dor pulsators. These two grids consider the distribution of initial rotation velocities at the zero-age main sequence deduced from gravito-inertial asteroseismology, for two extreme values found for the metallicity of γ Dor stars deduced from spectroscopy ([M/H]=0.0 and −0.5). Results. We find the new gravity-mode pulsators to cover an extended observational instability region covering masses from about 1.3 M⊙ to about 9 M⊙. We provide their mass-luminosity and mass-radius relations, as well as convective core masses. Our results suggest that oscillations excited by the opacity mechanism occur uninterruptedly for the mass range above about 2 M⊙, where stars have a radiative envelope aside from thin convection zones in their excitation layers. Conclusions. Our evolutionary parameters for the sample of Gaia-discovered gravity-mode pulsators with confirmed modes by TESS offer a fruitful starting point for future TESS ensemble asteroseismology once a sufficient number of modes is identified in terms of the geometrical wave numbers and overtone for each of the pulsators.

Chronological age estimation based on dental mineralization for Syrian population.

Dental age assessment based on evaluating dental mineralization status is one of the most common methods used in forensic practice. The aim of this study is to enhance the accuracy of age diagnostics and provide reference data from the Syrian population for forensic application. After several selection steps, a total of 280 orthopantomograms (OPGs) from 140 males and 140 females from the Syrian population divided into 14 age groups between 12 and 25 years were analysed. Based on Demirjian's classification system, the mineralization stages of third molars (18, 28, 38 and 48) as well as lower second molars (37 and 47) were evaluated. Statistical investigations and evaluations were carried out to estimate the marginal probabilities of the subjects having attained ages 14 and 18 by generalized estimating equation models. Our results show that no significant differences can be revealed in the mineralization status with respect to jaw side and sex. In the Syrian population, third molars showing mineralization stage G provide evidence of reaching the age of 14 years with the highest standard of proof ("beyond reasonable doubt"). A completed mineralization in lower second molars (stage H) provides very high marginal probabilities (more than 90%) of the subjects having attained age 14 years. Nevertheless, this cannot exclude an age under 14 years. For the age threshold of 18 years, third molars showing incomplete root development (G dental stage or lower) are associated with a low probability (less than 40%) of the subject having reached 18 years of age. A person's probability of having attained 18 years of age is very high (82- 95%) when the roots of third molars are fully developed (stage H). Nevertheless, third molars at stage H do not conclusively exclude an age under 18 years.

A biochronological date of 3.6 million years for "Little Foot" (StW 573, Australopithecus prometheus from Sterkfontein, South Africa).

A debate has developed with regard to geological ages of hominin fossils attributed to Australopithecus africanus and Australopithecus prometheus in South African Plio-Pleistocene cave deposits. For the Sterkfontein caves (Members 2 and 4), cosmogenic nuclide isochron (10Be/26Al) dating has yielded age estimates ranging from 3.4 to 3.7 million years ago (Ma). However, biochronological approaches using nonhominin primates suggest an alternative age range between 2 and 2.6 Ma. Based on a new method of hominin biochronology, Thackeray and Dykes have recognized that Sterkfontein Member 4 has a mean age of 2.76 Ma associated with a wide range (circa 2.0-3.5 Ma). In this study, the Sterkfontein skull and skeleton (StW 573), nicknamed "Little Foot" from Member 2 and attributed to A. prometheus, is reassessed. A regression model applied to estimate its age provides a hypothesized date of 3.6 Ma, which compares favorably with the existing cosmogenic dates.

Root canal widths of mandibular molars in predicting the legal age threshold 18 years in a sample of juveniles and sub-adults of south-indian origin: an orthopantomographic study.

Pursuing a proficient age estimation methodology introducing novel radiographic methods remains an ongoing and demanding aspect of forensic and medicolegal research. In 2017, Roberts GJ et al. (J Forensic Sci 62(2):351-4, 2017) described a new radiographic method, i.e., root canal width (RCW) patterns to assign a subject to above 18-year-age threshold. Since then, few researchers have investigated the validity of this radiographic method in other populations. The present study aimed to test the usefulness of these RCW patterns in predicting 18 years in a sample of South Indian juveniles and sub-adults aged between 16 and 23. Descriptive analysis revealed that pattern-A was initially observed at a minimum age of 16.08 and 16.22 years in males and females. Pattern-B at 16.31 years in males and 16.22 years in females, while pattern-C was initially recorded at 18.73 years in males and 19.01 years in females, respectively. In summary, if an individual, regardless of sex, exhibits a fully-formed (apex closed) mandibular first, second, and third molars and concurrently displays RCW-C, there is a strong likelihood that the person has exceeded the legally relevant age of 18 years. However, due to higher rate of technically unacceptable errors (adults wrongly identified as individuals below 18 years), reliance on this method alone should be restricted, and it is advisable to combine it with other methods.

Applications of artificial intelligence in age estimation: a review

Age estimation is a legally significant issue, particularly in underdeveloped and developing countries, due to factors such as inadequate civil registration systems and irregular migration. While various techniques are employed for age estimation using traditional methods, it is known that factors including age, gender, chronic illness, race, and geographical region can result in discrepancies between skeletal age and chronological age. This complicates the process of achieving accurate age estimation. This review aims to discuss recent research on artificial intelligence applications in light of current literature. Artificial intelligence and machine learning have enabled machines to acquire human-like capabilities in thinking, learning, problem solving, and decision making, leading to significant progress in achieving faster and accurate results. In the field of forensic medicine, methods such as linear discriminant analysis, K-Nearest Neighbors, support vector machines, random forests, and artificial neural networks have been employed to classify data and conduct studies on age estimation. Research has focused on five regions: the carpal bones, ossification centers, the middle phalanx of the hand, the third metacarpal, and the radius and ulna. Additionally, facial angles and width obtained through tomographic examinations, as well as measurements of the calcaneus and cuboid bones, panoramic dental radiographs, volumetric analysis of teeth and pulp using Cone Beam Computed Tomography, and analysis of bloodstains on microRNAs, have been analyzed for their distribution across different age. The results demonstrate that artificial intelligence applications can be utilized in age estimation with a high accuracy rate (85-95%). Age estimation using artificial intelligence enhances data-driven decision-making processes, improves the quality of services, and contributes to societal benefit. Therefore, we believe that incorporating artificial intelligence applications alongside traditional methods in age estimation will yield more meaningful outcomes.

The Hungarian fossil record of the Pliocene pig Sus arvernensis (Suidae, Mammalia)

Sus arvernensis is a Pliocene species that occupies a key position in the evolution of suids (Suidae, Artiodactyla, Mammalia) in Eurasia, and besides, it is considered important for biochronological correlations and paleoecological inferences. However, our knowledge on S. arvernensis is largely based on fossil remains from southwestern Europe. Here, we present a revision of the Hungarian fossil record of S. arvernensis. Up to now, the species was known from only two localities of Hungary, Gödöllő (central Hungary) and Süttő (northwest Hungary), and the latter occurrence has even been questioned. After the comparison with other relevant samples of S. arvernensis, of the Early Pleistocene S. strozzii, and of the extant wild boar S. scrofa (motivated by previous attributions and the chronology of the localities), the presence of S. arvernensis from Gödöllő and Süttő is confirmed, and more material of the species is described from Beremend (southern Hungary) and Kisláng (western Hungary). Collectively, the results of the revision carried out herein reveal a relatively widespread distribution of S. arvernensis in Hungary, hence providing an important link from the eastern to western European fossil record of the species. The specimens from Gödöllő and Süttő are slightly larger than the other material of S. arvernensis from France and Italy included in the biometric comparison, although the paucity of the material precludes to evaluate whether these differences are significant and to relate them to a chronological and/or geographical context. The occurrence of S. arvernensis in the Hungarian localities considered in this work is a biochronological indication of an age older than at least 2.6 Ma, since the species is not recorded after the Pliocene–Pleistocene transition. This in agreement with the age estimates available so far for some of the localities or provides new insights. At Süttő, in particular, the identification of S. arvernensis reinforces the view that travertine deposition started already in the Pliocene.

Prognostic assessment based on the trajectory of artificial intelligence-enabled electrocardiograms for age estimation

Abstract Background Artificial Intelligence (AI) estimation of age using data from the 12-lead electrocardiogram (ECG) has demonstrated its utility as a biomarker in predicting the future risk of cardiac diseases and mortality. However, expected long-term outcomes based on temporal changes in the AI-ECG age gap remain unclear. Purpose This study aims to utilize the difference between ages predicted by AI-ECG and actual ages longitudinally for follow-up and to assess whether there are significant clinical differences in mortality among specific groups. Methods Among patients at a hospital who had not been used for the AI-ECG age prediction model (121,702 individuals, 522,261 ECGs), 6,685 individuals with 31,858 ECGs who had an index ECG and the subsequent ECG in the fifth year, with at least one intervening ECG were included for analysis. The absolute age gap, defined as the absolute difference between ECG-predicted and chronological age, was limited to ±10 for analysis. Latent class trajectory modeling was then utilized to classify groups based on the AI-ECG age gap. Results Data-driven analysis revealed four distinct trajectory groups based on age gap trajectories: Consistently Young ECG (27.2%), Reversed ECG Aging (35.3%), Accelerated ECG Aging (8.0%), and Consistently Old ECG (29.5%). Notably, the Accelerated ECG Aging group exhibited a significantly higher cumulative incidence of all-cause death (adjusted hazard ratio (HR) 1.66 (95% confidence interval (CI) 1.30-2.12, p-value &amp;lt;0.001) and non-cardiac death (adjusted HR 1.83 (95% CI 1.38-2.43, p-value &amp;lt;0.001) compared to the Consistently Young ECG group. Conclusion Among 4 distinct trajectories based on the changes in the AI-ECG age gap, Accelerated ECG Aging was associated with a heightened risk of all-cause mortality. Additional in-depth analysis of factors associated with Accelerated ECG Aging is warranted.

Assessing Blue Catfish population dynamics across varying introduction timelines in Georgia

AbstractObjectiveUnderstanding the dynamic rate functions of introduced fish populations is essential in guiding management strategies. Blue Catfish Ictalurus furcatus population dynamics have been well studied; however, there is a gap in knowledge from populations that have been introduced into novel systems.MethodsBlue Catfish were collected from the Altamaha, Ocmulgee, Oconee, and Satilla rivers in Georgia. Age estimates were obtained through otolith analysis. Multimodel growth analysis was used to describe growth patterns, and early life growth was modeled with linear regression. Instantaneous mortality of each population was estimated and compared by using a generalized linear model approach.ResultThe four introduced Blue Catfish populations exhibited rapid growth and low mortality rates during establishment; however, we found that populations with earlier introduction histories generally had slower growth rates and lower mortality. The Satilla River population is comparatively the most recently introduced population (first discovered in 2011) that exhibited the fastest growth and highest mortality.ConclusionOur results suggest that Blue Catfish in our study systems are in an intermediate stage of invasion and have not yet reached an equilibrium state. As density continues to increase in these river systems, we expect a decline in growth rates, delayed sexual maturation, and a greater observed maximum age. However, additional monitoring is needed to identify how population dynamics and reproductive characteristics vary over time.

Assessing the utility of computer vision for age determination of Gulf Menhaden

AbstractObjectiveIn this work, we assess the potential of computer vision techniques for age estimation of Gulf Menhaden Brevoortia patronus scales. Scales are the primary structure used for the age determination of Gulf Menhaden, and the ageing process can be labor intensive. Gulf Menhaden is the second‐largest fishery by weight in the United States, with average annual landings from 2018 to 2022 of 449,540 metric tons, and is assessed with age‐structured models that require information about the age structure of the catch and the stock.MethodsWe used convolutional neural networks and deep neural networks to classify the age from images of Gulf Menhaden scales from three different sets of images of scales. The first set of data consists of images of scales from fish at ages 0 and 1 year. The second set of data consists of images of scales from fish at ages 0–4 years. The last set of data consists of images of scales from fish of ages 0, 1, and 2 years and includes only images of scales for which there is agreement by readers of age estimates derived from analyzing sagittal otoliths and scales from the same individual.ResultThe classification of ages was best when using a convolutional neural network model on the first data set. The poorest classification was for the model using deep neural networks with the second data set.ConclusionAlthough we show that computer vision has promise for age determination from fish scale samples, our results indicate that considerable work must be done for wide adoption of the approach. With the continuous enhancements of computer vision models, improvements in the quality of scale images, and the accumulation of larger sets of scale images that can be used to train machine learning models, we believe that using computer vision can serve to reduce processing time and increase the accuracy of age estimates.

Charting the growth through intelligence: A SWOC analysis on AI-assisted radiologic bone age estimation.

Bone age estimation (BAE) is based on skeletal maturity and degenerative process of the skeleton. The clinical importance of BAE is in understanding the pediatric and growth-related disorders; whereas medicolegally it is important in determining criminal responsibility and establishing identification. Artificial Intelligence (AI) has been used in the field of the field of medicine and specifically in diagnostics using medical images. AI can greatly benefit the BAE techniques by decreasing the intra observer and inter observer variability as well as by reducing the analytical time. The AI techniques rely on object identification, feature extraction and segregation. Bone age assessment is the classical example where the concepts of AI such as object recognition and segregation can be used effectively. The paper describes various AI based algorithms developed for the purpose of radiologic BAE and the performances of the models. In the current paper we have also carried out qualitative analysis using Strength, Weakness, Opportunities and Challenges (SWOC) to examine critical factors that contribute to the application of AI in BAE. To best of our knowledge, the SWOC analysis is being carried out for the first time to assess the applicability of AI in BAE. Based on the SWOC analysis we have provided strategies for successful implementation of AI in BAE in forensic and medicolegal context.