CADe and CADx systems for the detection and diagnosis of lung cancer have been important areas of research in recent decades. However, these areas are being worked on separately. CADe systems do not present the radiological characteristics of tumors, and CADx systems do not detect nodules and do not have good levels of automation. As a result, these systems are not yet widely used in clinical settings. The purpose of this article is to develop a new system for detection and diagnosis of pulmonary nodules on CT images, grouping them into a single system for the identification and characterization of the nodules to improve the level of automation. The article also presents as contributions: the use of Watershed and Histogram of oriented Gradients (HOG) techniques for distinguishing the possible nodules from other structures and feature extraction for pulmonary nodules, respectively. For the diagnosis, it is based on the likelihood of malignancy allowing more aid in the decision making by the radiologists. A rule-based classifier and Support Vector Machine (SVM) have been used to eliminate false positives. The database used in this research consisted of 420 cases obtained randomly from LIDC-IDRI. The segmentation method achieved an accuracy of 97 % and the detection system showed a sensitivity of 94.4 % with 7.04 false positives per case. Different types of nodules (isolated, juxtapleural, juxtavascular and ground-glass) with diameters between 3 mm and 30 mm have been detected. For the diagnosis of malignancy our system presented ROC curves with areas of: 0.91 for nodules highly unlikely of being malignant, 0.80 for nodules moderately unlikely of being malignant, 0.72 for nodules with indeterminate malignancy, 0.67 for nodules moderately suspicious of being malignant and 0.83 for nodules highly suspicious of being malignant. From our preliminary results, we believe that our system is promising for clinical applications assisting radiologists in the detection and diagnosis of lung cancer.

The goal of this paper is to present a critical review of major Computer-Aided Detection systems (CADe) for lung cancer in order to identify challenges for future research. CADe systems must meet the following requirements: improve the performance of radiologists providing high sensitivity in the diagnosis, a low number of false positives (FP), have high processing speed, present high level of automation, low cost (of implementation, training, support and maintenance), the ability to detect different types and shapes of nodules, and software security assurance. The relevant literature related to “CADe for lung cancer” was obtained from PubMed, IEEEXplore and Science Direct database. Articles published from 2009 to 2013, and some articles previously published, were used. A systemic analysis was made on these articles and the results were summarized. Based on literature search, it was observed that many if not all systems described in this survey have the potential to be important in clinical practice. However, no significant improvement was observed in sensitivity, number of false positives, level of automation and ability to detect different types and shapes of nodules in the studied period. Challenges were presented for future research. Further research is needed to improve existing systems and propose new solutions. For this, we believe that collaborative efforts through the creation of open source software communities are necessary to develop a CADe system with all the requirements mentioned and with a short development cycle. In addition, future CADe systems should improve the level of automation, through integration with picture archiving and communication systems (PACS) and the electronic record of the patient, decrease the number of false positives, measure the evolution of tumors, evaluate the evolution of the oncological treatment, and its possible prognosis.

O Transtorno do Espectro Autista (TEA) é um distúrbio complexo do desenvolvimento, desencadeado por uma interação entre fatores genéticos e ambientais que se manifesta principalmente através de alterações neurológicas, comportamentais e digestivas. As abordagens nutricionais emergem como uma perspectiva promissora para mitigar tais sintomas. Este estudo procurou encontrar evidências científicas sobre intervenções nutricionais em pré-escolares com TEA, especialmente em relação aos sintomas gastrointestinais e/ou comportamentais comuns no transtorno. Foi realizada uma revisão integrativa a fim de responder à pergunta: há evidências científicas que estabeleçam uma relação entre o TEA e a terapia nutricional, favorecendo melhorias nos sinais e sintomas em pré-escolares? Foram analisados artigos de janeiro de 2018 a janeiro de 2024, seguindo as recomendações do The Joanna Briggs Institute, utilizando as bases de dados Medline/Pubmed, Embase, Cochrane Library e Scopus. Seis estudos foram incluídos, abrangendo diferentes tipos de intervenções nutricionais. Destacam-se intervenções com dietas sem glúten, suplementos alimentares de vitamina A, D, Ômega 3, soro de leite rico em cisteína e probióticos. Concluiu-se que a intervenção nutricional pode trazer benefícios para sintomatologia do TEA, enfatizando a necessidade de mais pesquisas para entender melhor esta relação com o transtorno.

Healthcare services and organizations rely on Electronic Health Records (EHRs) to manage, store, and transmit patient data records. Consequently, EHRs play a crucial role in providing high-quality services and maintaining the privacy and security of patients' sensitive data. However, designing such complex systems with security and privacy concerns is anything but simple. This study aims to propose a software reference architecture (SRA) tailored for Electronic Health Records (EHRs) with security and privacy considerations, intending to enhance the development of these systems. To achieve this goal, we analyze the classification of reference architectures (RAs), taking into account the primary security and privacy requirements of EHRs along with well-established architectural design methods. We propose a layered architecture for SRA with privacy and security considerations. Subsequently, we derive the following five architecture views for SRA: the feature diagram, the context diagram, the decomposition view, the layered view, and the deployment view. Each view showcases the SRA software architecture from a different perspective.Moreover, we conducted an evaluation of the proposed SRA through its application in a case study. Specifically, we applied the proposed SRA and derived the application architecture from a study focused on Brazilian EHRs. Our analysis highlights the potential issues arising from the absence of an SRA tailored for EHRs, particularly regarding privacy and security concerns surrounding patient data. Through this case study, we demonstrate the practical applicability of our proposed SRA in enhancing EHR systems.