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1.
J Robot Surg ; 18(1): 150, 2024 Apr 02.
Artigo em Inglês | MEDLINE | ID: mdl-38564025

RESUMO

Pedicle screw placement (PSP) is the fundamental surgical technique that requires high accuracy for novice orthopedists studying spinal oncology education. Therefore, we set forth to establish a computer-assisted robotic navigation training program for novice spinal oncology education. Novice orthopedists were involved in this study to evaluate the feasibility and safety of the computer-assisted robotic navigation (CARN) training program. In this research, trainees were randomly taught by the CARN training program and the traditional training program. We prospectively collected the clinical data of patients with spinal tumors from 1st May 2021 to 1st March 2022. The ability of PSP was evaluated by cumulative sum (CUSUM) analysis, learning curve, and accuracy of pedicle screws. The patients included in both groups had similar baseline characteristics. In the CUSUM analysis of the learning curve for accurate PSP, the turning point in the CARN group was lower than that in the traditional group (70th vs. 92nd pedicle screw). The LC-CUSUM test indicated competency for PSP at the 121st pedicle screw in the CARN group and the 138th pedicle screw in the traditional group. The accuracy of PSP was also significantly higher in the CARN group than in the traditional group (88.17% and 79.55%, P = 0.03 < 0.05). Furthermore, no major complications occurred in either group. We first described CARN in spinal oncology education and indicated the CARN training program as a novel, efficient and safe training program for surgeons.


Assuntos
Parafusos Pediculares , Procedimentos Cirúrgicos Robóticos , Cirurgiões , Humanos , Procedimentos Cirúrgicos Robóticos/métodos , Curva de Aprendizado , Computadores
2.
Sci Rep ; 14(1): 8071, 2024 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-38580700

RESUMO

Over recent years, researchers and practitioners have encountered massive and continuous improvements in the computational resources available for their use. This allowed the use of resource-hungry Machine learning (ML) algorithms to become feasible and practical. Moreover, several advanced techniques are being used to boost the performance of such algorithms even further, which include various transfer learning techniques, data augmentation, and feature concatenation. Normally, the use of these advanced techniques highly depends on the size and nature of the dataset being used. In the case of fine-grained medical image sets, which have subcategories within the main categories in the image set, there is a need to find the combination of the techniques that work the best on these types of images. In this work, we utilize these advanced techniques to find the best combinations to build a state-of-the-art lumber disc herniation computer-aided diagnosis system. We have evaluated the system extensively and the results show that the diagnosis system achieves an accuracy of 98% when it is compared with human diagnosis.


Assuntos
Deslocamento do Disco Intervertebral , Humanos , Deslocamento do Disco Intervertebral/diagnóstico por imagem , Diagnóstico por Computador/métodos , Algoritmos , Aprendizado de Máquina , Computadores
3.
PLoS One ; 19(4): e0286795, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38568953

RESUMO

Computers and the Internet are widely recognized as fundamental to academic and future success on both the individual and the societal level. Moreover, the academic success of school-age children is now increasingly tied to access to educational technology, a reality that became even more apparent during the pandemic. While academic performance is viewed as the major outcome of using educational technology, this study looks at a crucial early stage in the educational technology value chain, specifically; 1) to what extent do students use computers and the Internet in their homes and at school and 2) what is the extent and nature of disparities in student access to educational technology. This study was conducted using the national CPS 2019 Computer and Internet Use Survey of 23,064 school age children. We used bivariate tables and multivariate logistic regression analysis to analyze the data. Results indicate that substantial disparities in the use of educational technology exist in the U.S. Overall, 28.0% of school age children reported they did not use the Internet at school or at home and another 22.8% reported using the Internet at home but not at school. Significantly, individual and community demographic characteristics and household and school technology resources contribute to these disparities. It is clear that if fundamental educational technology and the resources needed to effectively achieve academic success are unavailable in the home, then they must be provided in schools. Without educational technology and resources, the societal value added through growing use of this technology will not materialize for our students. We conclude that committing to increasing educational technology resources in the schools will have multiple future societal benefits and improve the effectiveness of the educational technology value chain.


Assuntos
Exclusão Digital , Criança , Humanos , Escolaridade , Computadores , Instituições Acadêmicas , Estudantes
4.
Ann Plast Surg ; 92(4S Suppl 2): S271-S274, 2024 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-38556688

RESUMO

BACKGROUND: Following the integration of the electronic health record (EHR) into the healthcare system, concern has grown regarding EHR use on physician well-being. For surgical residents, time spent on the EHR increases the burden of a demanding, hourly restricted schedule and detracts from time spent honing surgical skills. To better characterize these burdens, we sought to describe EHR utilization patterns for plastic surgery residents. METHODS: Integrated plastic surgery resident EHR utilization from March 2019 to March 2020 was extracted via Cerner Analytics at a tertiary academic medical center. Time spent in the EHR on-duty (0600-1759) and off-duty (1800-0559) in the form of chart review, orders, documentation, and patient discovery was analyzed. Statistical analysis was performed in the form of independent t tests and Analysis of Variance (ANOVA). RESULTS: Twelve plastic surgery residents spent a daily average of 94 ± 84 minutes on the EHR, one-third of which was spent off-duty. Juniors (postgraduate years 1-3) spent 123 ± 99 minutes versus seniors (postgraduate years 4-6) who spent 61 ± 49 minutes (P < 0.01). Seniors spent 19% of time on the EHR off-duty, compared with 37% for juniors (P < 0.01). Chart review comprised the majority (42%) of EHR usage, followed by patient discovery (22%), orders (14%), documentation (12%), other (6%), and messaging (1%). Seniors spent more time on patient discovery (25% vs 21%, P < 0.001), while juniors spent more time performing chart review (48% vs 36%, P = 0.19). CONCLUSION: Integrated plastic surgery residents average 1.5 hours on the EHR daily. Junior residents spend 1 hour more per day on the EHR, including more time off-duty and more time performing chart review. These added hours may play a role in duty hour violations and detract from obtaining operative skill sets.


Assuntos
Internato e Residência , Cirurgia Plástica , Humanos , Registros Eletrônicos de Saúde , Fatores de Tempo , Computadores
5.
Front Public Health ; 12: 1307592, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38577273

RESUMO

Introduction: Mechanical neck pain has become prevalent among computer professionals possibly because of prolonged computer use. This study aimed to investigate the relationship between neck pain intensity, anthropometric metrics, cervical range of motion, and related disabilities using advanced machine learning techniques. Method: This study involved 75 computer professionals, comprising 27 men and 48 women, aged between 25 and 44 years, all of whom reported neck pain following extended computer sessions. The study utilized various tools, including the visual analog scale (VAS) for pain measurement, anthropometric tools for body metrics, a Universal Goniometer for cervical ROM, and the Neck Disability Index (NDI). For data analysis, the study employed SPSS (v16.0) for basic statistics and a suite of machine-learning algorithms to discern feature importance. The capability of the kNN algorithm is evaluated using its confusion matrix. Results: The "NDI Score (%)" consistently emerged as the most significant feature across various algorithms, while metrics like age and computer usage hours varied in their rankings. Anthropometric results, such as BMI and body circumference, did not maintain consistent ranks across algorithms. The confusion matrix notably demonstrated its classification process for different VAS scores (mild, moderate, and severe). The findings indicated that 56% of the pain intensity, as measured by the VAS, could be accurately predicted by the dataset. Discussion: Machine learning clarifies the system dynamics of neck pain among computer professionals and highlights the need for different algorithms to gain a comprehensive understanding. Such insights pave the way for creating tailored ergonomic solutions and health campaigns for this population.


Assuntos
Vértebras Cervicais , Cervicalgia , Masculino , Humanos , Feminino , Adulto , Cervicalgia/diagnóstico , Medição da Dor/métodos , Computadores
6.
PLoS One ; 19(4): e0299021, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38593148

RESUMO

Developing chaotic systems-on-a-chip is gaining much attention due to its great potential in securing communication, encrypting data, generating random numbers, and more. The digital implementation of chaotic systems strives to achieve high performance in terms of time, speed, complexity, and precision. In this paper, the focus is on developing high-speed Field Programmable Gate Array (FPGA) cores for chaotic systems, exemplified by the Lorenz system. The developed cores correspond to numerical integration techniques that can extend to the equations of the sixth order and at high precision. The investigation comprises a thorough analysis and evaluation of the developed cores according to the algorithm complexity and the achieved precision, hardware area, throughput, power consumption, and maximum operational frequency. Validations are done through simulations and careful comparisons with outstanding closely related work from the recent literature. The results affirm the successful creation of highly efficient sixth-order Lorenz discretizations, achieving a high throughput of 3.39 Gbps with a precision of 16 bits. Additionally, an outstanding throughput of 21.17 Gbps was achieved for the first-order implementation coupled with a high precision of 64 bits. These outcomes set our work as a benchmark for high-performance characteristics, surpassing similar investigations reported in the literature.


Assuntos
Algoritmos , Computadores , Comunicação
7.
BMC Bioinformatics ; 25(1): 127, 2024 Mar 25.
Artigo em Inglês | MEDLINE | ID: mdl-38528499

RESUMO

BACKGROUND: N6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotic cells that plays a crucial role in regulating various biological processes, and dysregulation of m6A status is involved in multiple human diseases including cancer contexts. A number of prediction frameworks have been proposed for high-accuracy identification of putative m6A sites, however, none have targeted for direct prediction of tissue-conserved m6A modified residues from non-conserved ones at base-resolution level. RESULTS: We report here m6A-TCPred, a computational tool for predicting tissue-conserved m6A residues using m6A profiling data from 23 human tissues. By taking advantage of the traditional sequence-based characteristics and additional genome-derived information, m6A-TCPred successfully captured distinct patterns between potentially tissue-conserved m6A modifications and non-conserved ones, with an average AUROC of 0.871 and 0.879 tested on cross-validation and independent datasets, respectively. CONCLUSION: Our results have been integrated into an online platform: a database holding 268,115 high confidence m6A sites with their conserved information across 23 human tissues; and a web server to predict the conserved status of user-provided m6A collections. The web interface of m6A-TCPred is freely accessible at: www.rnamd.org/m6ATCPred .


Assuntos
Adenosina , Computadores , Humanos , Aprendizado de Máquina , Processamento Pós-Transcricional do RNA
8.
J Biomed Inform ; 152: 104617, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38432534

RESUMO

OBJECTIVE: Machine learning methods hold the promise of leveraging available data and generating higher-quality data while alleviating the data collection burden on healthcare professionals. International Classification of Diseases (ICD) diagnoses data, collected globally for billing and epidemiological purposes, represents a valuable source of structured information. However, ICD coding is a challenging task. While numerous previous studies reported promising results in automatic ICD classification, they often describe input data specific model architectures, that are heterogeneously evaluated with different performance metrics and ICD code subsets. This study aims to explore the evaluation and construction of more effective Computer Assisted Coding (CAC) systems using generic approaches, focusing on the use of ICD hierarchy, medication data and a feed forward neural network architecture. METHODS: We conduct comprehensive experiments using the MIMIC-III clinical database, mapped to the OMOP data model. Our evaluations encompass various performance metrics, alongside investigations into multitask, hierarchical, and imbalanced learning for neural networks. RESULTS: We introduce a novel metric, , tailored to the ICD coding task, which offers interpretable insights for healthcare informatics practitioners, aiding them in assessing the quality of assisted coding systems. Our findings highlight that selectively cherry-picking ICD codes diminish retrieval performance without performance improvement over the selected subset. We show that optimizing for metrics such as NDCG and AUPRC outperforms traditional F1-based metrics in ranking performance. We observe that Neural Network training on different ICD levels simultaneously offers minor benefits for ranking and significant runtime gains. However, our models do not derive benefits from hierarchical or class imbalance correction techniques for ICD code retrieval. CONCLUSION: This study offers valuable insights for researchers and healthcare practitioners interested in developing and evaluating CAC systems. Using a straightforward sequential neural network model, we confirm that medical prescriptions are a rich data source for CAC systems, providing competitive retrieval capabilities for a fraction of the computational load compared to text-based models. Our study underscores the importance of metric selection and challenges existing practices related to ICD code sub-setting for model training and evaluation.


Assuntos
Registros Eletrônicos de Saúde , Classificação Internacional de Doenças , Humanos , Redes Neurais de Computação , Aprendizado de Máquina , Computadores , Codificação Clínica/métodos
9.
J Robot Surg ; 18(1): 104, 2024 Mar 02.
Artigo em Inglês | MEDLINE | ID: mdl-38430388

RESUMO

PURPOSE: Computer-navigated (CN) total hip arthroplasty (THA) offers improved acetabular component placement and radiographic outcomes, but inconsistent assessment methods of its learning curves render the evaluation of adopting a novel platform challenging. Therefore, we conducted a systematic review to assess the learning curve associated with CN-THA, both tracking a surgeon's performance across initial cases and comparing their performance to manual THA (M-THA). METHODS: A search was conducted using PubMed, MEDLINE, EBSCOhost, and Google Scholar on June 16, 2023 to find research articles published after January 1, 2000 (PROSPERO registration: CRD4202339403) that investigated the learning curve associated with CN-THA. 655 distinct articles were retrieved and subsequently screened for eligibility. In the final analysis, nine publications totaling 847 THAs were evaluated. The Methodological Index for Nonrandomized Studies (MINORS) tool was utilized to evaluate the potential for bias, with the mean MINORS score of 21.3 ± 1.2. RESULTS: CN-THA showed early advantages to M-THA for component placement accuracy and radiographic outcomes but longer operative times (+ 3- 20 min). There was a learning curve required to achieve peak proficiency in these metrics, though mixed methodologies made the required caseload unclear. CONCLUSIONS: CN-THA offers immediate advantages to M-THA for component placement accuracy and radiographic outcomes, though CN-THA's advantages become more pronounced with experience. Surgeons should anticipate longer operative times during the learning curve for CN-THA, which lessen following a modest caseload. A more thorough evaluation of novel computer-navigated technologies would be enhanced by adopting a more uniform method of defining learning curves for outcomes of interest. Registration PROSPERO registration of the study protocol: CRD42023394031, 27 June 2023.


Assuntos
Artroplastia de Quadril , Procedimentos Cirúrgicos Robóticos , Humanos , Artroplastia de Quadril/métodos , Curva de Aprendizado , Procedimentos Cirúrgicos Robóticos/métodos , Resultado do Tratamento , Computadores
10.
Sci Rep ; 14(1): 7570, 2024 03 30.
Artigo em Inglês | MEDLINE | ID: mdl-38555360

RESUMO

Pressure monitoring in various organs of the body is essential for appropriate diagnostic and therapeutic purposes. In almost all situations, monitoring is performed in a hospital setting. Technological advances not only promise to improve clinical pressure monitoring systems, but also engage toward the development of fully implantable systems in ambulatory patients. Such systems would not only provide longitudinal time monitoring to healthcare personnel, but also to the patient who could adjust their way-of-life in response to the measurements. In the past years, we have developed a new type of piezoresistive pressure sensor system. Different bench tests have demonstrated that it delivers precise and reliable pressure measurements in real-time. The potential of this system was confirmed by a continuous recording in a patient that lasted for almost a day. In the present study, we further characterized the functionality of this sensor system by conducting in vivo implantation experiments in nine female farm pigs. To get a step closer to a fully implantable system, we also adapted two different wireless communication solutions to the sensor system. The communication protocols are based on MICS (Medical Implant Communication System) and BLE (Bluetooth Low Energy) communication. As a proof-of-concept, implantation experiments in nine female pigs demonstrated the functionality of both systems, with a notable technical superiority of the BLE.


Assuntos
Computadores , Próteses e Implantes , Humanos , Feminino , Animais , Suínos , Monitorização Fisiológica/métodos
11.
Comput Methods Programs Biomed ; 248: 108113, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38479148

RESUMO

BACKGROUND AND OBJECTIVE: In recent years, Artificial Intelligence (AI) and in particular Deep Neural Networks (DNN) became a relevant research topic in biomedical image segmentation due to the availability of more and more data sets along with the establishment of well known competitions. Despite the popularity of DNN based segmentation on the research side, these techniques are almost unused in the daily clinical practice even if they could support effectively the physician during the diagnostic process. Apart from the issues related to the explainability of the predictions of a neural model, such systems are not integrated in the diagnostic workflow, and a standardization of their use is needed to achieve this goal. METHODS: This paper presents IODeep a new DICOM Information Object Definition (IOD) aimed at storing both the weights and the architecture of a DNN already trained on a particular image dataset that is labeled as regards the acquisition modality, the anatomical region, and the disease under investigation. RESULTS: The IOD architecture is presented along with a DNN selection algorithm from the PACS server based on the labels outlined above, and a simple PACS viewer purposely designed for demonstrating the effectiveness of the DICOM integration, while no modifications are required on the PACS server side. Also a service based architecture in support of the entire workflow has been implemented. CONCLUSION: IODeep ensures full integration of a trained AI model in a DICOM infrastructure, and it is also enables a scenario where a trained model can be either fine-tuned with hospital data or trained in a federated learning scheme shared by different hospitals. In this way AI models can be tailored to the real data produced by a Radiology ward thus improving the physician decision making process. Source code is freely available at https://github.com/CHILab1/IODeep.git.


Assuntos
Aprendizado Profundo , Sistemas de Informação em Radiologia , Inteligência Artificial , Computadores , Software
12.
Korean J Radiol ; 25(4): 343-350, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38528692

RESUMO

OBJECTIVE: Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings. MATERIALS AND METHODS: From March 2020 to May 2022, 656 breasts from 599 women (mean age 52.6 ± 11.5 years, including 0.6% [4/599] high-risk women) who underwent mammography and received positive AI-CAD results (Lunit Insight MMG, abnormality score ≥ 10) were retrospectively included in this study. Univariable and multivariable analyses were performed to evaluate the associations between the AI-CAD abnormality scores and clinical and radiological factors. The breasts were subdivided according to the abnormality scores into groups 1 (10-49), 2 (50-69), 3 (70-89), and 4 (90-100) using the optimal binning method. The PPVs were calculated for all breasts and subgroups. RESULTS: Diagnostic indications and positive imaging findings by radiologists were associated with higher abnormality scores in the multivariable regression analysis. The overall PPV of AI-CAD was 32.5% (213/656) for all breasts, including 213 breast cancers, 129 breasts with benign biopsy results, and 314 breasts with benign outcomes in the follow-up or diagnostic studies. In the screening mammography subgroup, the PPVs were 18.6% (58/312) overall and 5.1% (12/235), 29.0% (9/31), 57.9% (11/19), and 96.3% (26/27) for score groups 1, 2, 3, and 4, respectively. The PPVs were significantly higher in women with diagnostic indications (45.1% [155/344]), palpability (51.9% [149/287]), fatty breasts (61.2% [60/98]), and certain imaging findings (masses with or without calcifications and distortion). CONCLUSION: PPV increased with increasing AI-CAD abnormality scores. The PPVs of AI-CAD satisfied the acceptable PPV range according to Breast Imaging-Reporting and Data System for screening mammography and were higher for diagnostic mammography.


Assuntos
Neoplasias da Mama , Mamografia , Feminino , Humanos , Adulto , Pessoa de Meia-Idade , Mamografia/métodos , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/patologia , Valor Preditivo dos Testes , Estudos Retrospectivos , Inteligência Artificial , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Detecção Precoce de Câncer , Computadores
13.
J Neuroeng Rehabil ; 21(1): 37, 2024 03 19.
Artigo em Inglês | MEDLINE | ID: mdl-38504351

RESUMO

BACKGROUND: Children with unilateral cerebral palsy (UCP) are encouraged to participate in the regular school curriculum. However, even when using the less-affected hand for handwriting, children with UCP still experience handwriting difficulties. Visual-motor integration (VMI) is a predictor of handwriting quality. Investigating VMI in children with UCP is important but still lacking. Conventional paper-based VMI assessments is subjective and use all-or-nothing scoring procedures, which may compromise the fidelity of VMI assessments. Moreover, identifying important shapes that are predictive of VMI performance might benefit clinical decision-making because different geometric shapes represent different developmental stepping stones of VMI. Therefore, a new computer-aided measure of VMI (the CAM-VMI) was developed to investigate VMI performance in children with UCP and to identify shapes important for predicting their VMI performance. METHODS: Twenty-eight children with UCP and 28 typically-developing (TD) children were recruited. All participants were instructed to complete the CAM-VMI and Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery-VMI). The test items of the CAM-VMI consisted of nine simple geometric shapes related to writing readiness. Two scores of the CAM-VMI, namely, Error and Effort, were obtained by image registration technique. The performances on the Beery-VMI and the CAM-VMI of children with UCP and TD children were compared by independent t-test. A series of stepwise regression analyses were used to identify shapes important for predicting VMI performance in children with UCP. RESULTS: Significant group differences were found in both the CAM-VMI and the Beery-VMI results. Furthermore, Error was identified as a significant aspect for predicting VMI performance in children with UCP. Specifically, the square item was the only significant predictor of VMI performance in children with UCP. CONCLUSIONS: This study was a large-scale study that provided direct evidence of impaired VMI in school-aged children with UCP. Even when using the less-affected hand, children with UCP could not copy the geometric shapes as well as TD children did. The copied products of children with UCP demonstrated poor constructional accuracy and inappropriate alignment. Furthermore, the predictive model suggested that the constructional accuracy of a copied square is an important predictor of VMI performance in children with UCP.


Assuntos
Paralisia Cerebral , Desenvolvimento Infantil , Criança , Humanos , Desempenho Psicomotor , Computadores , Mãos
14.
Sci Rep ; 14(1): 6881, 2024 03 22.
Artigo em Inglês | MEDLINE | ID: mdl-38519515

RESUMO

Taphonomic works aim at discovering how paleontological and archaeofaunal assemblages were formed. They also aim at determining how hominin fossils were preserved or destroyed. Hominins and other mammal carnivores have been co-evolving, at least during the past two million years, and their potential interactions determined the evolution of human behavior. In order to understand all this, taxon-specific carnivore agency must be effectively identified in the fossil record. Until now, taphonomists have been able to determine, to some degree, hominin and carnivore inputs in site formation, and their interactions in the modification of part of those assemblages. However, the inability to determine agency more specifically has hampered the development of taphonomic research, whose methods are virtually identical to those used several decades ago (lagged by a high degree of subjectivity). A call for more objective and agent-specific methods would be a major contribution to the advancement of taphonomic research. Here, we present one of these advances. The use of computer vision (CV) on a large data set of images of tooth marks has enabled the objective discrimination of taxon-specific carnivore agency up to 88% of the testing sample. We highlight the significance of this method in an interdisciplinary interplay between traditional taphonomic-paleontological analysis and artificial intelligence-based computer science. The new questions that can be addressed with this will certainly bring important changes to several ideas on important aspects of the human evolutionary process.


Assuntos
Carnívoros , Hominidae , Dente , Animais , Humanos , Inteligência Artificial , Osso e Ossos , Fósseis , Computadores
15.
Prim Dent J ; 13(1): 64-73, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38424692

RESUMO

AIM: This paper provides a comprehensive review of the established concepts and newer developments related to computer-assisted implant rehabilitation. METHODS: Two independent researchers searched the English literature published to 31st December 2023 in the PubMed/Medline database for primary and secondary research and related publications on computer-assisted implant planning, computer-assisted implant placement and computer-assisted implant restoration. RESULTS: A total of 58,923 papers were identified, 198 relevant papers were read in full text and 110 studies were finally included. Computer-assisted implant rehabilitation was found to result in more precise implant positioning than freehand placement. Advantages include reduced trauma and surgery time; disadvantages include reduced primary implant stability and higher cost. CONCLUSION: Computer-assisted surgery is particularly indicated in cases of critical anatomy, but may encounter limitations in terms of cost, restricted mouth opening, visibility and adjustment of the surgical guides and the need for prior familiarisation with the procedure. Nonetheless, this surgical technique reduces the post-implant placement complication rate.


Assuntos
Implantes Dentários , Cirurgia Assistida por Computador , Humanos , Implantação Dentária Endóssea/métodos , Tomografia Computadorizada de Feixe Cônico , Computadores , Desenho Assistido por Computador
16.
Cereb Cortex ; 34(3)2024 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-38436466

RESUMO

The debate on whether computer gaming enhances players' cognitive function is an ongoing and contentious issue. Aiming to delve into the potential impacts of computer gaming on the players' cognitive function, we embarked on a brain imaging-derived phenotypes (IDPs)-wide Mendelian randomization (MR) study, utilizing publicly available data from a European population. Our findings indicate that computer gaming has a positive impact on fluid intelligence (odds ratio [OR] = 6.264, P = 4.361 × 10-10, 95% confidence interval [CI] 3.520-11.147) and cognitive function (OR = 3.322, P = 0.002, 95% CI 1.563-7.062). Out of the 3062 brain IDPs analyzed, only one phenotype, IDP NET100 0378, was significantly influenced by computer gaming (OR = 4.697, P = 1.10 × 10-5, 95% CI 2.357-9.361). Further MR analysis suggested that alterations in the IDP NET100 0378 caused by computer gaming may be a potential factor affecting fluid intelligence (OR = 1.076, P = 0.041, 95% CI 1.003-1.153). Our MR study lends support to the notion that computer gaming can facilitate the development of players' fluid intelligence by enhancing the connectivity between the motor cortex in the resting-state brain and key regions such as the left dorsolateral prefrontal cortex and the language center.


Assuntos
Análise da Randomização Mendeliana , Jogos de Vídeo , Encéfalo/diagnóstico por imagem , Cognição , Computadores , Inteligência , Fenótipo , Neuroimagem
17.
PLoS One ; 19(3): e0299549, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38489336

RESUMO

Insulin secretion from pancreatic ß-cells is integral in maintaining the delicate equilibrium of blood glucose levels. Calcium is known to be a key regulator and triggers the release of insulin. This sub-cellular process can be monitored and tracked through live-cell imaging and subsequent cell segmentation, registration, tracking, and analysis of the calcium level in each cell. Current methods of analysis typically require the manual outlining of ß-cells, involve multiple software packages, and necessitate multiple researchers-all of which tend to introduce biases. Utilizing deep learning algorithms, we have therefore created a pipeline to automatically segment and track thousands of cells, which greatly reduces the time required to gather and analyze a large number of sub-cellular images and improve accuracy. Tracking cells over a time-series image stack also allows researchers to isolate specific calcium spiking patterns and spatially identify those of interest, creating an efficient and user-friendly analysis tool. Using our automated pipeline, a previous dataset used to evaluate changes in calcium spiking activity in ß-cells post-electric field stimulation was reanalyzed. Changes in spiking activity were found to be underestimated previously with manual segmentation. Moreover, the machine learning pipeline provides a powerful and rapid computational approach to examine, for example, how calcium signaling is regulated by intracellular interactions.


Assuntos
Cálcio , Processamento de Imagem Assistida por Computador , Processamento de Imagem Assistida por Computador/métodos , Algoritmos , Computadores , Microscopia de Fluorescência/métodos
18.
Comput Biol Med ; 172: 108204, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38484695

RESUMO

S6K2 is an important protein in mTOR signaling pathway and cancer. To identify potential S6K2 inhibitors for mTOR pathway treatment, a virtual screening of 1,575,957 active molecules was performed using PLANET, AutoDock GPU, and AutoDock Vina, with their classification abilities compared. The MM/PB(GB)SA method was used to identify four compounds with the strongest binding energies. These compounds were further investigated using molecular dynamics (MD) simulations to understand the properties of the S6K2/ligand complex. Due to a lack of available 3D structures of S6K2, OmegaFold served as a reliable 3D predictive model with higher evaluation scores in SAVES v6.0 than AlphaFold, AlphaFold2, and RoseTTAFold2. The 150 ns MD simulation revealed that the S6K2 structure in aqueous solvation experienced compression during conformational relaxation and encountered potential energy traps of about 19.6 kJ mol-1. The virtual screening results indicated that Lys75 and Lys99 in S6K2 are key binding sites in the binding cavity. Additionally, MD simulations revealed that the ligands remained attached to the activation cavity of S6K2. Among the compounds, compound 1 induced restrictive dissociation of S6K2 in the presence of a flexible region, compound 8 achieved strong stability through hydrogen bonding with Lys99, compound 9 caused S6K2 tightening, and the binding of compound 16 was heavily influenced by hydrophobic interactions. This study suggests that these four potential inhibitors with different mechanisms of action could provide potential therapeutic options.


Assuntos
Proteínas Quinases S6 Ribossômicas 70-kDa , Serina-Treonina Quinases TOR , Fosforilação , Proteínas Quinases S6 Ribossômicas 70-kDa/metabolismo , Serina-Treonina Quinases TOR/metabolismo , Computadores
19.
Sci Rep ; 14(1): 7386, 2024 03 28.
Artigo em Inglês | MEDLINE | ID: mdl-38548856

RESUMO

This study aimed to conduct a cross-sectional data analysis of the alveolar bone mineral density (al-BMD) in 225 patients of various ages and different sexes. The al-BMD value in the mandibular incisor region was calculated using a computer-aided measurement system (DentalSCOPE) for intraoral radiography. All participants with intact teeth (101 males and 124 females; age range, 25-89 years) were divided into three age-segregated groups (25-49, 50-74, and > 75 years). Statistical differences were evaluated using the Mann-Whitney U or Kruskal-Wallis test. Males exhibited significantly greater al-BMD than females (p < 0.001). The highest means were observed in the 25-49 age group, regardless of sex (1007.90 mg/cm2 in males, 910.90 mg/cm2 in females). A 9.8% decrease in al-BMD was observed with the increase in age in males (25-49 to 50-74 years; p = 0.004); however, no further changes were seen thereafter. In females, a decreasing trend was seen throughout the lifespan, with values reaching up to 76.0% of the initial peak value (p < 0.001). Similar to other skeletal sites, the alveolar bone exhibits sex differences and undergoes a reduction in BMD via the normal aging process.


Assuntos
Densidade Óssea , Caracteres Sexuais , Humanos , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Estudos Transversais , Radiografia , Computadores , Absorciometria de Fóton
20.
Med Pr ; 75(1): 69-80, 2024 Mar 22.
Artigo em Polonês | MEDLINE | ID: mdl-38523502

RESUMO

Analyses of the economic activity of the Polish population indicate that in 2023, about 7% of all employees performed, usually or sometimes, their work in the form of remote work. The purpose of this publication is to analyze the impact of working with screen-monitor devices on computer vision syndromes, musculoskeletal disorders, circadian rhythm, and to identify recommendations for the proper organization of the home office. A narrative review of the existing literature on the impact of work with the use of devices equipped with screen monitors on the health of employees was performed, as well as recommendations in the above-mentioned area were presented. The most important factors determining the load on the visual organs and musculoskeletal system and affecting the overall health and well-being of employees during remote work are the proper arrangement of the workstation (in accordance with ergonomic principles) and the organization of work (limiting the time spent working at the computer/laptop, systematic active breaks) and healthy sleep habits. It is crucial that both employers, occupational health professionals and employees themselves are aware of the importance to their health of correct preparation of the home office, and have adequate knowledge in this regard. Med Pr Work Health Saf. 2024;75(1):69-80.


Assuntos
Doenças Musculoesqueléticas , Doenças Profissionais , Saúde Ocupacional , Humanos , Teletrabalho , Ergonomia/métodos , Computadores , Doenças Musculoesqueléticas/prevenção & controle , Doenças Profissionais/prevenção & controle , Doenças Profissionais/epidemiologia
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