Aid Of Technology Research Articles

Automated Detection of Breast Lump/ Masses through Mammogram Image Analysis

Current technology is playing a key role in the field of health care. As everything is getting automated here is an attempt to automate the identification of lumps in the breast. Lump in the breast can be a sign of breast cancer. The uncontrolled growth of breast cells is the reason for lumps or cancer in the breast. Not all lumps in the breasts are cancer. Still early identification and staging of the disease is critical in planning the treatment of breast cancer. In late stages malignancy can extend beyond the breast and spread to surrounding structures. Mammogram is the gold standard procedure in the diagnosis of carcinoma of breast cancer. In this article we have made an attempt to spot out the lump in the breast with the aid of technology. We have also attempted to extend our work to identify the stage of the cancer.

V-CarE-A Conceptual Design Model for Providing COVID-19 Pandemic Awareness: Proposal for a Virtual Reality Design Approach to Facilitate People With Persistent Postural-Perceptual Dizziness.

Virtual reality (VR) technology has been solidifying its ground since its existence, where engagement and a sense of presence are key. The contemporary field of development has captured the attention of researchers due to its flexibility and compatibility attributes. During the COVID-19 pandemic, several research outputs have shown promising prospects of continuing research in the field of VR design and development-in health sciences including learning and training. In this paper, we aim to propose a conceptual development model named V-CarE (Virtual Care Experience) that can facilitate the understanding of pandemics when it comes to a crisis, taking precautionary measures where needed, and getting used to certain actions for preventing pandemic spread through habituation. Moreover, this conceptual model is useful to expand the development strategy to incorporate different types of users and technological aid as per need and requirement. For a detailed understanding of the proposed model, we have developed a novel design strategy to bring awareness to the user about the current COVID-19 pandemic. VR research in health sciences has shown that with appropriate management and development, VR technology can efficiently support people with health issues and special needs, which motivated our attempts to explore the possibility of employing our proposed model to treat Persistent Postural-Perceptual Dizziness (PPPD)-a persistent nonvertiginous dizziness that could last for 3 months or more. The purpose of including patients with PPPD is to get them engaged in the learning experience and to make them comfortable with VR. We believe this confidence and habituation would help them get engaged with VR for treatment (dizziness alleviation) while practicing the preventive measures during the pandemic in an interactive environment without actually facing any pandemic directly. Subsequently, for advanced development using the V-CarE model, we have briefly discussed that even contemporary technology like internet of things (IoT) for handling devices, can be incorporated without disrupting the complete 3D-immersive experience. In our discussion, we have shown that the proposed model represents a significant step toward the accessibility of VR technology by creating a pathway toward awareness of pandemics and, also, an effective care strategy for PPPD people. Moreover, by introducing advanced technology, we will only further enhance the development for wider accessibility of VR technology while keeping the core purpose of the development intact. V-CarE-based developed VR projects are designed with all the core elements of health sciences, technology, and training making it accessible and engaging for the users and improving their lifestyle by safely experiencing the unknown. We suggest that with further design-based research, the proposed V-CarE model has the potential to be a valuable tool connecting different fields to wider communities.

Technologically assisted intensive home treatment: feasibility study.

In recent year, many attempts have been made to provide patients with alternatives to psychiatric hospitalization during acute distress. Although several hospitalization alternatives have been offered, most of them still require patients to be distanced from their families, friends, and the social environment. In this report we describe the implementation of a novel approach to psychiatric care termed "Technologically assisted Intensive Home Treatment", where patients arriving to emergency settings are directed to home care with technological aids that enable close monitoring and ongoing contact with their therapists. We describe the rationale and treatment principles of the treatment, and provide an elaborative description of the implementation process during the first year of implementation. Additional attention is given to factors associated with early dropout from the program, in order to inform readers of predictors to optimal care. Limitations and directions for future research and practice are discussed.Clinical Trial Registration: The study was registered in the database of clinical trials (registration number SHEBA-19-6555-MW-CTIL) and in the Ministry of Health (registration number MOH_2022-08-22_011992).

FORMATION OF STUDENTS’ MOTIVATION IN MASTERING PATHOMORPHOLOGY DISCIPLINE

Abstract. Motivation is an essential factor of human activity, which, in turn, determines the development and efficiency of activities, including the educational process. A contradiction was revealed between the objective need to form the motivation of cognitive activity of students of a medical higher education institution (HEI) through the introduction of interactive technologies considering both the internal features of learning and external requirements for medical university-educated specialists – on the one hand, and the lack of scientifically grounded technology for forming the motivation of a medical HEI students’ cognitive activity using the latest systems – on the other hand.
 The main factor influencing students’ motivation to study is mastering of knowledge, skills and abilities that will lay the groundwork of their future professional activities. Students engaged in research are motivated to self-development and achievement. These are the ones that make students work hard, solve complex problems, engage in self-education, and overcome difficulties to achieve the highest results.
 The article presents the ways and methods of formation the students’ motivation when mastering the Pathomorphology discipline.
 In order to improve ways and methods of students’ motivating, we analysed scientific sources on the specifics of professional and educational activity motivation, the principles of educational process organisation at the Pathological Anatomy Department.
 Under trying circumstances of today, every applicant for higher education has the opportunity to obtain a full range of information on the Pathomorphology discipline on the Pathological Anatomy Department website and in the university repository for productive self-training and mastering practical skills and abilities provided by the discipline’s programme. To increase motivation in the study of pathomorphology and the level of assimilation of the material. The department uses general and special innovative methods that depend on the specifics of studying the discipline: explanatory-illustrative (informational-receptive), contextual, problematic, research, heuristic. Different strategies should be used to encourage students to become more intrinsically motivated, developing their sense of competence and control over their learning, and to motivate students with interesting content.
 Under present-day conditions, teaching Pathomorphology requires constant improvement in compliance with medicine development level and the ability to combine classical approaches to teaching with new learning concepts. The decline in traditional teaching methods efficiency, which is observed when considering the peculiarities of students’ learning activities, requires correction and implementation of modern innovative teaching methods. Improving the methods of learning motivation will help to increase the level of study material mastery. Applying new information technology and technical aids in distance and blended learning makes it possible to demonstrate and study morphological changes in pathological processes and diseases, which in turn will maximise the level of learning material mastering. The variety of illustrative material (macro preparations, micro preparations, breadboard models, 3-D models, training charts and diagrams, videos) taken in a whole lays the foundation of basic knowledge. Engaging students in research work is an important factor in learning activities motivating.

Impact of Digital Finance on Manufacturing Technology Innovation: Fixed-Effects and Panel-Threshold Approaches

Digital finance (DF) has provided important financial support for the transformation and upgrading of China’s manufacturing industry. Innovation is the engine of industrial upgrading. To solve the dilemma of developing the manufacturing industry, it is necessary to enhance independent innovation capabilities. On this basis, this article studies the impact of DF on manufacturing technology innovation (MTI). It uses the data of listed manufacturing firms in the Shenzhen and Shanghai A-share markets from 2011 to 2020 to establish a fixed-effects model and a panel-threshold model for empirical analysis. The results revealed that, first, DF significantly accelerates technological innovation in manufacturing enterprises and has a significant positive impact on technological innovation. Secondly, DF drives manufacturing enterprises’ technological innovation by alleviating financial constraints (FCs). Thirdly, there is a dual-threshold effect based on market competition between DF and MTI based on market competition, and the promotion effect of DF on technology innovation decreases with the increasing degree of market competition. Finally, DF better enhances the technological innovation of non-state-owned manufacturing firms in the respective regions compared to state-owned firms. In terms of factor-intensive types, DF is more able to advance the innovative technologies of labor-intensive and capital-intensive enterprises, while it has no significant positive effect on technology-intensive enterprises. Policy implications are suggested to boost manufacturing technology innovation and aid future studies.

A pilot study for testing a low-cost 3D design with an inertial sensor for the quantitative assessment of finger tapping in patients with Parkinson's Disease.

Parkinson's disease (PD) is one of the most common neurodegenerative disorders worldwide. Current identification and monitoring of its motor symptoms depends on the clinical expertise. Repetitive finger tapping is one of the most common clinical maneuvers to assess for bradykinesia. Despite the increasing use of technology aids to quantitatively characterize the motor symptoms of PD, there is still a relative lack of clinical evidence to support their widespread use, particularly in low-resource settings. In this pilot study, we used a low-cost design prototype coupled with an inertial sensor is coupled to quantify the frequency of the finger tapping movements in four participants with PD. Repetitive finger tapping was performed using both hands before and after taking levodopa as part of their clinical treatment. The proposed 3D design allowed repetitive movements to be performed without issues. The maximum frequency of finger tapping was in the range of 0.1 to 4.3 Hz. Levodopa was associated with variable changes in the maximum frequency of finger tapping. This pilot study shows the feasibility for low-cost technology to quantitatively characterize repetitive movements in people living with PD.Clinical relevance- In this pilot study, a low-cost inertial sensor coupled to a design prototype was feasible to characterize the frequency of repetitive finger tapping movements in four participants with PD. This method could be used to quantitatively identify and monitor bradykinesia in people living with PD.

A review of actor-oriented capitals and investments in the field of interpreting in Türkiye

This study aims to reveal the significance of the habitus and capitals of interpreters in Türkiye and the investments made to acquire such capital, and by employing a descriptive approach through the framework of Bourdieu's Field Theory and Latour's Actor-Network Theory (ANT) (1999). Within the scope of our study, Bourdieu’s concepts of habitus and capital have been used to discuss the position of interpreters in the field in Türkiye. Using a historical perspective, we will discuss the “actants” i.e. human and non-human actors that have played an influential role since the emergence of the profession in Türkiye. According to the ANT, it could be concluded that in Türkiye, these actors may consist not only of individuals but also of agents such as organizations such as TKTD and Türkiye AIIC VEGA, remote working conditions that have become widespread with Covid-19, and volunteering movements that emerged after the 2023 Kahramanmaraş earthquakes. During the research process of this study, sources such as interviews, webinars held on virtual platforms, newspaper clippings, the online archives of TKTD, and memories shared in books, theses and books on the history of translation and interpreting have been explored. Following our research, it has been determined the first interpreters in Türkiye acquired similar capitals and habituses, whereas present interpreters that accumulate different types of capitals depending on current circumstances and needs such as use of technology and first aid knowledge for community interpreting. Our study shows that the valued capitals play a key role in determining the position of actants in academia and the interpreting sector, resulting in a new dynamic between actants with the network.

The Boundaries of Legal Personhood: Disability, Gender and the Cyborg

By considering the death of the disability activist Engracia Figueroa as the consequence of her wheelchair being damaged by an airline, this article asks whether law could accommodate a definition of legal personhood that encompasses the possibility of bodies augmented by prosthetics, technology, and mobility aids. The use of mobility aids by disabled people and the role of prosthetic penises in so-called ‘gender fraud’ cases offer two useful provocations to consider the ways in which legal personhood, if defined as largely mapping on to an ideal, normative body, is becoming an increasingly inadequate legal concept in the modern age. Drawing on the work of Donna Haraway and the figure of the cyborg, this article argues that a more protean, flexible, and fluctuating understanding of legal personhood would offer both a more accurate and utopian conception of the body in law than the current essentialist approach found in a number of legal areas and particularly in English criminal law.

Visualisation and prediction of Covid-19 data using random forest regression

The outbreak of COVID-19 has spread among several parts of the world. The data pool increases tremendously, which needs excellent attention by researchers of various domains to analyze and determine the measures to handle it. Hence, researchers worldwide are looking into Artificial Intelligence (AI) to resolve the challenges due to this COVID-19. It could be stated that AI can examine huge data mounds so that several new findings can be determined. AI could be deployed in various fields, such as the pharmaceutical industry, the analysis and development of vaccines and antibodies, and drug designing. Due to the impressive progress that AI has made in the latest few years, still, it proves to be the essential quality of the technology and evidence of humans' creativity towards the contribution of developing tools and products which could be statistically and computationally complex. It is observed that AI technology aids in tracing the outburst, patient diagnosis and fastening the procedure of finding a treatment. This work provides an overview of COVID-19, along with the convergence of technologies that could be applied in various sections to handle this pandemic. An extensive exploration of multiple techniques and models has been implemented for the prediction of COVID-19 has been done. Additionally, numerous models have been deployed for predictions of covid states. It has been inferred that XGBoost showed considerable progress in the prophecy.

An efficient chain code for access control in hyper ledger fabric healthcare system

The emergence of eHealth has been instrumental in enhancing healthcare systems, offering improved health services to diverse patients with the aid of cutting-edge technologies. The safe and effective collection, transmission, and accessibility of electronic health records (EHRs) using modern information and communication technologies (ICTs) is essential for realizing the goals of eHealth. However, the use of EHRs by healthcare practitioners creates the risk of data breaches and jeopardizes patient confidentiality. Fortunately, smart contracts and blockchain technology offer effective EHR access control techniques that can enable secure client identification, authentication, and authorization, enhancing the security of EHRs.So, this paper brings effective Blockchain-based solutions using Hyperledger fabric for providing privacy to EHRs. An effective deployment architecture and chain code were generated for design and access control. In this case, the utilization of Hyperledger Fabric as the Blockchain technology introduces a new consensus mechanism, enabling efficient scalability and safeguarding anonymity. By employing Hyperledger Fabric for framework development, the system achieves its objectives. Experimental results are carried out for analyzing the system performance and also computational tests.

Discovering superhard high‐entropy diboride ceramics via a hybrid data‐driven and knowledge‐enabled model

AbstractMaterials descriptors with multivariate, multiphase, and multiscale of a complex system have been treated as the remarkable materials genome, addressing the composition–processing–structure–property–performance (CPSPP) relationships during the development of advanced materials. With the aid of high‐performance computations, big data, and artificial intelligence technologies, it is still a challenge to derive an explainable machine learning (ML) model to reveal the underlying CPSPP relationship, especially, under the extreme conditions. This work supports a smart strategy to derive an explainable model of composition–property–performance relationships via a hybrid data‐driven and knowledge‐enabled model, and designing superhard high‐entropy diboride ceramics (HEBs) with a cost‐effective approach. Five dominate features and optimal model were screened out from 149 features and nine algorithms by ML and validated in first‐principles calculations. From Shapley additive explanations (SHAP) and electronic bottom layer, the predicted hardness increases with the improved mean electronegativity and electron work function (EWF) and decreases with growing average d valence electrons of composition. The 14 undeveloped potential superhard HEBs candidates via ML are further validated by first‐principles calculations. Moreover, this EWF‐ML model not only has better capability to distinguish the differences of solutes in same group of periodic table but is also a more effective method for material design than that of valence electron concentration.

FACTORS INFLUENCING THE ATTITUDES OF SECONDARY SCHOOL STUDENTS TOWARDS THE STUDY OF MATHEMATICS.

It is a known fact that there exist behavioral difficulties among Mathematics students in Estiwani as a result of unresolved attitudinal issues that either the students are not aware of, or that the issues are not properly dealt with. This work seeks to investigate some factors influencing the attitude of secondary school students toward studying Mathematics in the Manzini region. Five schools consisting of two boys-only, two girls-only, and one mixed school were been carefully selected for the investigation. A total of 200 students and 15 qualified teachers were randomly and actively engaged. A combination of the discrete and continuous data collected through observations and using a well-designed questionnaire was carefully analyzed from their graphical representations. It was found that the majority of the students showed a huge gap in the content knowledge and also presented a clear negative attitude towards Mathematics as a subject. Some of the factors responsible for this worrying pattern, as shown by the analysis include poor background from their primary schools, ineffective teaching methods by their teachers, and lack of motivation by their parents among others. Training programs for teachers particularly on the use of technology and teaching aids to better disseminate the contents and the rewards were also highlighted.

Accuracy of Femoral Tunnel Localization With Mixed Reality Technology-Assisted Single-Bundle ACL Reconstruction.

It is clinically challenging to accurately drill femoral and tibial tunnels to reconstruct the anterior cruciate ligament (ACL). Mixed reality (MR) technology, a further development of virtual reality technology, presents virtual scene information in real time and establishes an interactive feedback information loop among the real world, the virtual world, and the user. The purpose of this study was to investigate the structural and early clinical outcomes of ACL reconstruction assisted by MR technology. It was hypothesized that MR technology would improve the accuracy of tunnel localization. Cohort study; Level of evidence, 3. Included were 44 patients at a single institution who underwent arthroscopic single-bundle ACL reconstruction between June 2020 and March 2022. Reconstruction with the aid of MR technology was performed in 21 patients (MR group), and conventional arthroscopic reconstruction was performed in 23 patients. Postoperatively, the parameters related to the bone tunnel positioning were compared by computed tomography imaging with 3-dimensional (3D) reconstruction, and 12-month postoperative clinical outcomes were assessed with the Lysholm and International Knee Documentation Committee scores. There was no statistically significant difference in projection angles in the coronal, axial, or sagittal plane between the preoperative virtually created tunnel guide pin and the actual tunnel (P > .05 for all). In the MR group, the center of the femoral tunnel exit was closer to the apex of the lateral femoral condyle along the proximal-distal axis (14.07 ± 4.12 vs 17.49 ± 6.24 mm for the conventional group; P < .05) and the graft bending angle was lower (117.71° ± 8.08° vs 127.81° ± 11.91° for the conventional group; P < .05). The scatterplot of the femoral tunnel location distribution showed that the entrance and exit points in the MR group were more concentrated and closer to the ideal location of the preoperative design than in the conventional group. Patients in both groups had significant preoperative-to-postoperative improvement based on outcome scores (P < .001 for all), with no significant difference between groups. ACL reconstruction with the aid of MR technology allowed for more accurate positioning and orientation of the femoral tunnel during surgery when compared with conventional reconstruction.

Machine Learning (ML) diffusion in the design process: A study of Norwegian design consultancies

Traditionally, the design process has been performed by designers and developers with the aid of digital technologies. The proliferation of Machine Learning (ML) during the last years has been argued to boost the creative process of design. This includes simple tasks such as translating handwritten notes, suggesting layouts options but also more complex action possibilities like generation of new ideas and prototyping for their visualization. However, the discourse about ML in creative industries is in an early stage, and there is limited knowledge about its diffusion in the design process. In our case study of four Norwegian design consultancies, we found that inhibitors (lack of ML knowledge, lack of trust in ML outputs, and poor results provided in languages other than English) overweighted the enablers (identifying patterns in the transcriptions, checking the requirements). This limited the intentions of design consultancies to introduce ML and undermined its diffusion in their design process.

Multiclass blood cancer classification using deep CNN with optimized features

Breast cancer, lung cancer, skin cancer, and blood malignancies such as leukemia and lymphoma are just a few instances of cancer, which is a collection of cells that proliferate uncontrollably within the body. Acute lymphoblastic leukemia is of one the significant form of malignancy. The hematologists frequently makes an oversight while determining a blood cancer diagnosis, which requires an excessive amount of time. Thus, this research reflects on a novel method for the grouping of the leukemia with the aid of the modern technologies like Machine Learning and Deep Learning. The proposed research pipeline is occupied into some interconnected parts like dataset building, feature extraction with pre-trained Convolutional Neural Network (CNN) architectures from each individual images of blood cells, and classification with the conventional classifiers. The dataset for this study is divided into two identical categories, Benign and Malignant, and then reshaped into four significant classes, each with three subtypes of malignant, namely, Benign, Early Pre-B, Pre-B, and Pro-B. The research first extracts the features from the individual images with CNN models and then transfers the extracted features to the features selections such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and SVC Feature Selectors along with two nature inspired algorithms like Particle Swarm Optimization (PSO) and Cat Swarm Optimization (CSO). After that, research has applied the seven Machine Learning classifiers to accomplish the multi-class malignant classification. To assess the efficacy of the proposed architecture a set of experimental data have been enumerated and interpreted accordingly. The study discovered a maximum accuracy of 98.43% when solely using pre-trained CNN and classifiers. Nevertheless, after incorporating PSO and CSO, the proposed model achieved the highest accuracy of 99.84% by integrating the ResNet50 CNN architecture, SVC feature selector, and LR classifiers. Although the model has a higher accuracy rate, it does have some drawbacks. However, the proposed model may also be helpful for real-world blood cancer classification.

The potentiality of GIS for assessing soil pollution – A review

The assessment of soil pollution is only one instance where geographic information systems (GIS) have shown to be an invaluable tool in environmental management and assessment. Globally, there is growing worry over soil pollution since it can have catastrophic repercussions on plant, animal, and human life. A more in-depth understanding of the scope and severity of contamination is made possible by GIS, which offers a flexible and all-encompassing method to studying and assessing soil pollution. With the aid of GIS technology, precise maps of soil contamination may be produced by combining data from numerous sources, such as remote sensing, aerial photography, and ground surveys. This information can then be evaluated using a variety of techniques, such as spatial analysis, to pinpoint polluted areas, possible sources of pollution, and the effects they are most likely to have on the environment and human health. By making it easier to identify sensitive regions that need additional research or remediation, GIS can also help with the analysis of the risk of pollutant movement and dispersion. Comparing GIS to conventional methods for assessing soil pollution has various benefits. First of all, it enables a more thorough and in-depth examination of the degree and breadth of contamination, enabling the identification of locations that need urgent care. Second, it makes it easier for different stakeholders, such as environmental agencies, researchers, and policymakers, to share data and information, enabling better decision-making. Thirdly, it makes it possible to monitor and control soil contamination more effectively, allowing for the early detection of potential issues and the implementation of suitable corrective actions. In general, GIS technology is a useful tool for assessing soil pollution since it offers a more thorough and knowledgeable approach to environmental management. It is a crucial tool for environmental experts engaged in the assessment and control of soil pollution due to its capacity to combine different data sources, perform spatial analysis, and promote information sharing.

DIGITAL TECHNOLOGY BASED BUSINESS MODEL DESIGN ANALYSIS

This research investigates how digital technology aid in the development of new business models in the creative industries. A holistic business model framework was built through a thorough literature study, which was then utilized to assess empirical evidence from the creative industries. According to the findings, digital technology have permitted widespread changes in company structures, and several noteworthy patterns have emerged. However, the redesigned business models are frequently not 'new' in the sense of being unprecedented. Business model innovation primarily manifests itself in the use of digital technology to enable the deployment of a broader choice of business models than was previously available to a corporation. The increasing adoption of numerous business models as a portfolio inside one corporation is a key rising trend. This occurs in enterprises of all sizes when a single firm employs numerous business models to service distinct market groups, offer different products, or engage in multi-sided markets, or employs changing business models over time. A recursive learning process refines and extends the holistic business model framework, which can serve as a cognitive instrument for comprehending business models as well as a planning tool for business model improvements. The study advances our understanding of business model theory and how digital technologies enable business model innovation in the creative industries. Three new study topics for the future are emphasized.

Effects of Using Technology on the Academic Performance in Mathematics of the College Millennial Learners

The educational landscape has changed significantly with technology. It affects how people live, work, play, and learn, wherein technology has challenged how education is managed and the methods and strategies in teaching, particularly in mathematics. This research is experimental and employed the multi-group pretest–posttest design to assess the effects of using technology on college millennial students’ academic performance in mathematics. The control group was subjected to the lecture-discussion method without using technology, while another section served as the experimental group and was exposed to technology-based instructions. The questionnaire was used to gather data from the respondents to determine the extent level of the effect of technology on student’s academic performance in mathematics. The results of the post-test increased significantly, and the experimental group results increased is 2.58 percent higher than controlled group. Teaching using technologies enhanced the student’s academic performance in mathematics, and it was concluded that teaching with the aid of technology is better than lecture type or traditional teaching methods.

In the name of Asian solidarity: Sino–Japanese competition for technology diplomacy in Burma, 1955–1965

A decade after the 1955 Bandung Conference, China and Japan engaged in a competition for technological exports to Burma. 1 During this process, technocrats in Beijing and Tokyo mobilized non-governmental collaborators—local Chinese industrialists and Japanese businesses seeking overseas expansion—as proxies to maximize their technological output to Burma. The Burmese, on the other hand, used the competition between Beijing and Tokyo as a bargaining tool, and pressed the two regional powers to provide at Rangoon's request. The technical aid Burma received was also affected by its shifting visions for development. Factionalist struggles between 1958 and 1962 changed not only Burma's political landscape but also its leadership's mind-set regarding the economy: the nation moved away from aid-driven industrial modernization towards a self-reliant, agricultural economy based on limited foreign technologies. Consequently, the meaning of the term ‘technological aid’, though used throughout the decade, became flexible and indistinct, carrying vastly different connotations at different stages of the Burmese state-building process. In this way, Burma's experience as an aid-receiving country in Cold War Asia may speak to the flexible power dynamics between the aiding and the aided countries, and shed light on the diversified means through which states employed science and technology as diplomatic tools in Cold War competition.

Utility of line-field confocal optical coherence tomography in the pediatric population.

In the last decades diagnosis of dermatological diseases has achieved a significant progress with the aid of imaging technologies. In pediatric population dermatologic procedural investigations require special considerations, skill sets, and knowledge. Avoiding unnecessary invasive procedures in children is highly recommended to reduce psychological disturbance and cosmetical scars. Line-field confocal optical coherence tomography (LC-OCT) is an innovative, high-resolution, non-invasive imaging technique, that is proving to be valuable in the diagnosis of different skin conditions. In this study, we aimed to analyze the most common indications for LC-OCT in pediatric age group, discussing its potential role in clinical setting. A retrospective review of the medical charts of patients ≤18 years of age, who were performed clinical, dermoscopy and LC-OCT for equivocal skin lesions, was conducted. Diagnostic confidence level was calculated for clinical/dermoscopic diagnosis alone and for combined clinical/dermoscopy and LC-OCT findings, based on a three-point scale ranging from 0% to 100%. Seventy-four skin lesions in 73 patients [(39 (53.4%) females and 34 (46.6%) males, mean age 13.2 (range 5-18 years) years] were investigated with LC-OCT. Diagnosis was established with histopathology in 23/74 (31.1%) cases, while 51/74 (68.9%) skin lesions were monitored over time or treated with topical/physical therapy. High diagnostic confidence increased by 21.6% after LC-OCT assessment, meanwhile reducing low and average score. LC-OCT may add practical clues for the identification of common skin conditions in pediatric population, improving diagnostic confidence and consequent tailored approach.