STK3 higher expression association with clinical characteristics in intrinsic subtypes of breast cancer invasive ductal carcinoma patients.

PURPOSE: STK3 has a central role in maintaining cell homeostasis, proliferation, growth, and apoptosis. Previously, we investigated the functional link between STK3/MST2, and estrogen receptor in MCF-7 breast cancer cells. To expand the investigation, this study evaluated STK3's higher expression and associated genes in breast cancer intrinsic subtypes using publicly available data. METHODS: The relationship between clinical pathologic features and STK3 high expression was analyzed using descriptive and multivariate analysis. RESULTS: Increased STK3 expression in breast cancer was significantly associated with higher pathological cancer stages, and a different expression level was observed in the intrinsic subtypes of breast cancer. Kaplan-Meier analysis showed that breast cancer with high STK3 had a lower survival rate in IDC patients than that with low STK3 expression (p < 0.05). The multivariate analysis unveiled a strong correlation between STK3 expression and the survival rate among IDC patients, demonstrating hazard ratios for lower expression. In the TCGA dataset, the hazard ratio was 0.56 (95% CI 0.34-0.94, p = 0.029) for patients deceased with tumor, and 0.62 (95% CI 0.42-0.92, p = 0.017) for all deceased patients. Additionally, in the METABRIC dataset, the hazard ratio was 0.76 (95% CI 0.64-0.91, p = 0.003) for those deceased with tumor. From GSEA outcomes 7 gene sets were selected based on statistical significance (FDR < 0.25 and p < 0.05). Weighted Sum model (WSM) derived top 5% genes also have higher expression in basal and lower in luminal A in association with STK3. CONCLUSION: By introducing a novel bioinformatics approach that combines GSEA and WSM, the study successfully identified the top 5% of genes associated with higher expression of STK3.

Secondary findings in a large Pakistani cohort tested with whole genome sequencing.

Studies on genomic secondary findings (SFs) are diverse in participants' characteristics, sequencing methods, and versions of the ACMG SF list. Based on whole genome sequencing and the version 3.1 of the ACMG SF list, we studied SFs in 863 individuals from five different regions in Pakistan. We identified 24 ACMG SFs in 23 (2.7%) of 863 individuals: 18 of 24 were related to cardiovascular disease and four to cancer syndromes. In addition to ACMG SFs, we identified 16 (1.9%) participants with pathogenic and likely pathogenic variants in genes that were not related to the participants' clinical conditions but with clear medical actionability (non-ACMG SFs): 4 of 16 were related to eye diseases, two to metabolic disorders, and two to urinary system disorders. By testing a large Pakistani cohort with whole genome sequencing, we concluded that in countries such as Pakistan, the ACMG SF list could be expanded, and our non-ACMG SF list is one example.

Introducing ACTFAiREST2 to implement online assessments amid COVID-19: a case study from a low resource setting.

BACKGROUND: Amid COVID-19, soon after the closure of academic institutions, academia was compelled to implement teaching and assessments virtually. The situation was not the same for all countries. This transition was much more challenging in low-resource settings like Pakistan, where the students were geographically distant with minimal connectivity. A private university in Pakistan instituted a systematic approach for ensuring quality assurance and reliability before launching online assessments amid the COVID-19. The purpose of this study was to reflect on the phased transition to online/remote assessments to facilitate continuous student learning through distance modalities during the pandemic. METHOD: To assist faculty in re-designing their assessments, a workshop was conducted which was based on the modified Walker's nine principles. The principles coded as "ACTFAiREST2" were introduced to ensure that the faculty understands and adapts these principles in designing online assessments. The faculty modified and re-designed their course assessments, from face to face to online modality and submitted their proposals to the Curriculum Committee (CC). To guide the process of approving modified and re-designed assessments, a checklist was adapted. All the pre and -post workshop assessment proposals were analyzed using a content analysis approach to ensure the alignment of course learning outcomes with the assessments. RESULTS: A total of 45 undergraduate courses' assessment proposals were approved by the CC after deliberations ensuring their applicability in a virtual environment. From the analysis of the course outlines and assessment proposals submitted to the CC, faculty made four key changes to their assessment tasks in the light of ACT FAiREST2 principles (a) alternative to performance exams; (b) alternative to knowledge exams; (c) change in the mode of assessment administration; and (d) minimizing the overall assessment load. CONCLUSION: This transition provided an impetus for the faculty from a low resource setting to build momentum towards improved and innovative ways of online teaching and assessments for future nursing education to adapt to the new normal situation. This development will serve as a resource in similar contexts with planned and evidence-based approaches for enhancing faculty readiness and preparedness for online/remote assessments.

Diagnostic Value Of Serum Urea, Creatinine, Sodium And Potassium For Complicated Appendicitis - A One Year Retrospective Study.

BACKGROUND: Acute appendicitis is a common surgical emergency and if complicated, manifesting as abscess, perforation, suppurative or gangrenous appendicitis, carries significant morbidity and mortality. Its early preoperative diagnosis can improve outcome in patients and reduce incidence of negative appendectomies. It, however, mandates identification of new diagnostic parameters for it. This retrospective study evaluates diagnostic accuracy of serum urea, creatinine, sodium and potassium for complicated appendicitis. METHODS: Sixty patients with suspected appendicitis were grouped into complicated and uncomplicated appendicitis based on histological reports. Preoperative laboratory results for serum urea, creatinine, sodium and potassium levels were obtained from hospital records. Diagnostic strength of these markers was calculated as specificity, sensitivity and area under curve. ROC curve analysis was used for their diagnostic accuracy. RESULTS: The levels of serum urea, creatinine and K were not significantly different in uncomplicated and complicated appendicitis. However, sodium was significantly higher in complicated appendicitis. ROC curve analysis showed AUC values for all the studied variables to be greater than 0.5. However, none of the markers had good capability to differentiate complicated appendicitis from uncomplicated appendicitis. CONCLUSIONS: Serum urea, creatinine, sodium and potassium levels have shown a tendency to be predictive of complicated appendicitis but a strong association could not have been established. Hence, further investigation is warranted.

Comparison Of Efficacy Of Yogurt Versus Probiotics For The Management Of Acute Diarrhoea.

BACKGROUND: The advantages of probiotic administration for acute diarrhoea are mainly shorter duration of symptoms as well as reduced number of stools per day while use of traditional yogurt has similar results. So, this study was conducted to compare the efficacy of yogurt with probiotic in children with acute gastroenteritis. METHODS: This randomized controlled trial was conducted at department of Paediatrics, Children Hospital, Pakistan Institute of Medical Sciences, Islamabad over 1 year. A total of nine hundred and thirty (930) children between 1-5 years of age presenting with acute diarrhoea were enrolled and equally randomized to Group-A (yogurt) and Group-B (lactobacillus rhamnosus) with ORS. The primary outcome was mean frequency of diarrhoea in first 24 hours after initiation of treatment in both the groups. RESULTS: Gender distribution revealed that out of 930 patients, 643 (69.1%) were male and 287 (30.9%) were female while the mean age was 3.14±1.18 years. Mean duration of disease was 4.23±2.02 days. Mean no. of stools in first 24 hours after treatment in Group-A (yogurt) was 3.25±1.64 and 3.29±1.74 in Group-B (probiotics). Student t-test for independent samples was applied and no significant difference was found between the two groups (p=0.713). CONCLUSIONS: Mean frequency of diarrhoea in first 24 hours after treatment with traditional yogurt and commercially available probiotics was not statistically significant in this study.

Retention of knowledge regarding mathematics and drug dosage calculation among undergraduate nursing students of a private school of nursing in Pakistan.

This study aimed to assess the level of retention of knowledge regarding calculation of drug dose among undergraduate nursing students studying at a private school of nursing. This was a pre- and post-comparison design conducted at the Aga Khan University, Pakistan, from August 2017 to September 2019. All the students enrolled in Bachelor of Science in Nursing (BScN) (Class of 2019) were included in the study. Mean test scores of 141 fourth year BScN students were compared with their own performance in the second year. Mean scores on mathematics and drug dosage calculation test decreased significantly from 21 in second year to 17.97 in the final year of studies. Modifications in assessments as well as curriculum are suggested to improve retention of dose calculation skills among undergraduate nursing students.

COVID-19 Knowledge Resource Categorization and Tracking: Conceptual Framework Study.

BACKGROUND: Since the declaration of COVID-19 as a global pandemic by the World Health Organization, the disease has gained momentum with every passing day. Various private and government sectors of different countries allocated funding for research in multiple capacities. A significant portion of efforts has been devoted to information technology and service infrastructure development, including research on developing intelligent models and techniques for alerts, monitoring, early diagnosis, prevention, and other relevant services. As a result, many information resources have been created globally and are available for use. However, a defined structure to organize these resources into categories based on the nature and origin of the data is lacking. OBJECTIVE: This study aims to organize COVID-19 information resources into a well-defined structure to facilitate the easy identification of a resource, tracking information workflows, and to provide a guide for a contextual dashboard design and development. METHODS: A sequence of action research was performed that involved a review of COVID-19 efforts and initiatives on a global scale during the year 2020. Data were collected according to the defined structure of primary, secondary, and tertiary categories. Various techniques for descriptive statistical analysis were employed to gain insights into the data to help develop a conceptual framework to organize resources and track interactions between different resources. RESULTS: Investigating diverse information at the primary, secondary, and tertiary levels enabled us to develop a conceptual framework for COVID-19-related efforts and initiatives. The framework of resource categorization provides a gateway to access global initiatives with enriched metadata, and assists users in tracking the workflow of tertiary, secondary, and primary resources with relationships between various fragments of information. The results demonstrated mapping initiatives at the tertiary level to secondary level and then to the primary level to reach firsthand data, research, and trials. CONCLUSIONS: Adopting the proposed three-level structure allows for a consistent organization and management of existing COVID-19 knowledge resources and provides a roadmap for classifying future resources. This study is one of the earliest studies to introduce an infrastructure for locating and placing the right information at the right place. By implementing the proposed framework according to the stated guidelines, this study allows for the development of applications such as interactive dashboards to facilitate the contextual identification and tracking of interdependent COVID-19 knowledge resources.

Peer victimization and experiences of violence at school and at home among school age children with disabilities in Pakistan and Afghanistan.

Background: Children with disabilities are more likely to experience violence or injury at school and at home, but there is little evidence from Central Asia. Objective: To describe the prevalence of disability and associations with peer violence perpetration and victimization, depression, corporal punishment, school performance and school attendance, among middle school children in Pakistan and Afghanistan. Method: This is a secondary analysis of data gathered in the course of evaluations of interventions to prevent peer violence conducted in Pakistan and Afghanistan as part of the 'What Works to Prevent Violence against Women and Girls Global Programme'. In Pakistan, the research was conducted in 40 schools, and disability was assessed at midline in 1516 interviews with Grade 7s. In Afghanistan, the data were from the baseline study conducted in 11 schools with 770 children. Generalized Linear Mixed Modeling was used to assess associations with disability. Results: In Afghanistan, the prevalence of disability was much higher for girls (22.1%) than boys (12.9%), while in Pakistan 6.0% of boys and girls reported a disability. Peer violence victimization was strongly associated with disability in Afghanistan and marginally associated in Pakistan. In Pakistan, perpetration of peer violence was associated with disability. In both countries, disability was significantly associated with higher depression scores. Food insecurity was strongly associated with disability in Afghanistan. Conclusion: Disability is highly prevalent in Afghanistan and Pakistan schools and this is associated with a greater risk of experiencing and perpetrating peer violence. It is important to ensure that all children can benefit from school-based prevention interventions.

Clinical Decision Support System Based on Hybrid Knowledge Modeling: A Case Study of Chronic Kidney Disease-Mineral and Bone Disorder Treatment.

Clinical decision support systems (CDSSs) represent the latest technological transformation in healthcare for assisting clinicians in complex decision-making. Several CDSSs are proposed to deal with a range of clinical tasks such as disease diagnosis, prescription management, and medication ordering. Although a small number of CDSSs have focused on treatment selection, areas such as medication selection and dosing selection remained under-researched. In this regard, this study represents one of the first studies in which a CDSS is proposed for clinicians who manage patients with end-stage renal disease undergoing maintenance hemodialysis, almost all of whom have some manifestation of chronic kidney disease-mineral and bone disorder (CKD-MBD). The primary objective of the system is to aid clinicians in dosage prescription by levering medical domain knowledge as well existing practices. The proposed CDSS is evaluated with a real-world hemodialysis patient dataset acquired from Kyung Hee University Hospital, South Korea. Our evaluation demonstrates overall high compliance based on the concordance metric between the proposed CKD-MBD CDSS recommendations and the routine clinical practice. The concordance rate of overall medication dosing selection is 78.27%. Furthermore, the usability aspects of the system are also evaluated through the User Experience Questionnaire method to highlight the appealing aspects of the system for clinicians. The overall user experience dimension scores for pragmatic, hedonic, and attractiveness are 1.53, 1.48, and 1.41, respectively. A service reliability for the Cronbach's alpha coefficient greater than 0.7 is achieved using the proposed system, whereas a dependability coefficient of the value 0.84 reveals a significant effect.

Right To Play's intervention to reduce peer violence among children in public schools in Pakistan: a cluster-randomized controlled trial.

BACKGROUND: Peer violence is common globally, but a little researched topic in low-and middle-income countries. This study presents the evaluation of a two-year randomized controlled trial of a structured play-based life-skills intervention implemented in schools in Hyderabad, Pakistan. OBJECTIVE: To determine the impact of the intervention on school-based peer violence (victimization and perpetration) and depression among school children. METHODS: 40 single-sex public schools were randomized into two study arms (20 per arm 10 of each sex). A total of 1752 grade 6 students (929 from intervention and 823 from control schools) were enrolled in the trial. The two-year intervention was a biweekly structured game led by a coach followed by critical reflection and discussion for 30 minutes. Primary outcomes (exposure to peer violence exhibited through victimization and perpetration and depression) were evaluated using generalized linear-mixed models. RESULTS: Of the enrolled children (N = 1752) 91% provided data for analysis. There were significant decreases in self-reported peer violence victimization, perpetration and depression. For peer violence victimization, the reductions in the intervention and control arms were: 33.3% versus 27.8% for boys and 58.5% versus 21.3% for girls. For peer violence perpetration, the reductions were: 25.3% versus 11.1% for boys and 55.6% versus 27.6% for girls in the intervention and control arms, respectively. There were significant drops in mean depression scores (boys 7.2% versus 4.8% intervention and control and girls 9.5% versus 5.6% intervention and control). CONCLUSION: A well-designed and implemented play-based life-skills intervention delivered in public schools in Pakistan is able to effect a significant reduction in peer violence.

Community stakeholders' perspectives regarding acceptability of a life skills building intervention to empower women in Pakistan.

Violence against women (VAW) is a major determinant in the assessment of a women's mental health. Many interventions have addressed strategies to reduce VAW, however, little information is available regarding effectiveness in the local context, particularly the role of men in women's empowerment. In Pakistan, a qualitative approach was undertaken in all four of its provinces to describe the community residents', both men and women, perceptions regarding the acceptability of a proposed life skills building (LSB) intervention involving men's engagement with regards to women's empowerment and VAW. Eighteen focus group discussions were conducted with men and women from locales within each province of Pakistan, averaging 6-10 participants per group. Fourteen key informant interviews were conducted with community stakeholders. The analysis identified three major themes: family life and male engagement, LSB training as an empowerment tool, and operationalization of the proposed LSB intervention. The proposed LSB intervention was well accepted by the participants with a strong urge to engage men in receiving the LSB training sessions. Men's engagement has been identified as an important element to facilitate women's empowerment. Participants suggested that these sessions should be held for two and a half hours per week within the community public spaces. In addition, these sessions should be based on an interactive approach. The focus of these sessions should include ideas surrounding positive relationships and economic skills building. Moreover, men's engagement will help to reduce VAW and improve the mental health of women in a patriarchal country like Pakistan.

Acquiring guideline-enabled data driven clinical knowledge model using formally verified refined knowledge acquisition method.

BACKGROUND AND OBJECTIVE: Validation and verification are the critical requirements for the knowledge acquisition method of the clinical decision support system (CDSS). After acquiring the medical knowledge from diverse sources, the rigorous validation and formal verification process are required before creating the final knowledge model. Previously, we have proposed a hybrid knowledge acquisition method with the support of a rigorous validation process for acquiring medical knowledge from clinical practice guidelines (CPGs) and patient data for the treatment of oral cavity cancer. However, due to lack of formal verification process, it involves various inconsistencies in knowledge relevant to the formalism of knowledge, conformance to CPGs, quality of knowledge, and complexities of knowledge acquisition artifacts. METHODS: This paper presents the refined knowledge acquisition (ReKA) method, which uses the Z formal verification process. The ReKA method adopts the verification method and explores the mechanism of theorem proving using the Z notation. It enhances a hybrid knowledge acquisition method to thwart the inconsistencies using formal verification. RESULTS: ReKA adds a set of nine additional criteria to be used to have a final valid refined clinical knowledge model. These criteria ensure the validity of the final knowledge model concerning formalism of knowledge, conformance to GPGs, quality of the knowledge, usage of stringent conditions and treatment plans, and inconsistencies possibly resulting from the complexities. Evaluation, using four medical knowledge acquisition scenarios, shows that newly added knowledge in CDSS due to the additional criteria by the ReKA method always produces a valid knowledge model. The final knowledge model was also evaluated with 1229 oral cavity patient cases, which outperformed with an accuracy of 72.57% compared to a similar approach with an accuracy of 69.7%. Furthermore, the ReKA method identified a set of decision paths (about 47.8%) in the existing approach, which results in a final knowledge model with low quality, non-conformed from standard CPGs. CONCLUSION: ReKA refined the hybrid knowledge acquisition method by discovering the missing steps in the current validation process at the acquisition stage. As a formally proven method, it always yields a valid knowledge model having high quality, supporting local practices, and influenced by standard CPGs. Furthermore, the final knowledge model obtained from ReKA also preserves the performance such as the accuracy of the individual source knowledge models.

Community stakeholders' views on reducing violence against women in Pakistan.

BACKGROUND: Nearly half of the women experience violence across their lifespan in all the provinces of Pakistan at an alarming rate. Despite knowing the prevalence, there has been meager progress in developing strategies to combat violence at individual, family, or community level. Many interventions suggested in other countries have been pilot tested but the effects of those interventions had been limited. Therefore, the aim of this study is to understand the voices of stakeholders to reduce Violence Against Women (VAW) and to explore the possible community-based strategies that could be implemented in Pakistan. METHODS: A total of 14 Key Informant Interviews (KIIs) and 18 Focus Group Discussions (FGDs) were held across all four provinces of Pakistan. Participants were purposefully recruited and all the interviews were audio-recorded. Transcriptions were open coded and content analysis was done to emerge codes, categories and themes. Ethical approval was obtained from Aga Khan University Ethics Review Committee. RESULTS: Three major themes emerged on community members and stakeholders' views on VAW: a) community's perception of VAW b) the repercussions of VAW, and c) multiple voices regarding strategies to reduce VAW. Participants voiced the need of standing against the status quo, role of awareness and education: regarding capacity building skills, promotion of women rights and women empowerment through Life Skills Based Education (LSBE) through national health works program, has been proposed as an innovative strategy to reduce VAW. CONCLUSIONS: The responsibility to bring about a substantial change in behavior and attitudes must begin with engaging men in all the interventions that aim to reduce violence. Since, VAW is very much linked with the cultural norms, so, without community stakeholder's involvement and participation it could never be reduced. Keeping the existing socio-cultural dynamics in mind, the need of time is to design and implement innovative interventions that are culturally and contextually appropriate and can be expanded across the country.

Impact of Automatic Query Generation and Quality Recognition Using Deep Learning to Curate Evidence From Biomedical Literature: Empirical Study.

BACKGROUND: The quality of health care is continuously improving and is expected to improve further because of the advancement of machine learning and knowledge-based techniques along with innovation and availability of wearable sensors. With these advancements, health care professionals are now becoming more interested and involved in seeking scientific research evidence from external sources for decision making relevant to medical diagnosis, treatments, and prognosis. Not much work has been done to develop methods for unobtrusive and seamless curation of data from the biomedical literature. OBJECTIVE: This study aimed to design a framework that can enable bringing quality publications intelligently to the users' desk to assist medical practitioners in answering clinical questions and fulfilling their informational needs. METHODS: The proposed framework consists of methods for efficient biomedical literature curation, including the automatic construction of a well-built question, the recognition of evidence quality by proposing extended quality recognition model (E-QRM), and the ranking and summarization of the extracted evidence. RESULTS: Unlike previous works, the proposed framework systematically integrates the echelons of biomedical literature curation by including methods for searching queries, content quality assessments, and ranking and summarization. Using an ensemble approach, our high-impact classifier E-QRM obtained significantly improved accuracy than the existing quality recognition model (1723/1894, 90.97% vs 1462/1894, 77.21%). CONCLUSIONS: Our proposed methods and evaluation demonstrate the validity and rigorousness of the results, which can be used in different applications, including evidence-based medicine, precision medicine, and medical education.

Semantic preservation of standardized healthcare documents in big data.

BACKGROUND: Standardized healthcare documents have a high adoption rate in today's hospital setup. This brings several challenges as processing the documents on a large scale takes a toll on the infrastructure. The complexity of these documents compounds the issue of handling them which is why applying big data techniques is necessary. The nature of big data techniques can trigger accuracy/semantic loss in health documents when they are partitioned for processing. This semantic loss is critical with respect to clinical use as well as insurance, or medical education. METHODS: In this paper we propose a novel technique to avoid any semantic loss that happens during the conventional partitioning of healthcare documents in big data through a constraint model based on the conformance of clinical document standard and user based use cases. We used clinical document architecture (CDAR) datasets on Hadoop Distributed File System (HDFS) through uniquely configured setup. We identified the affected documents with respect to semantic loss after partitioning and separated them into two sets: conflict free documents and conflicted documents. The resolution for conflicted documents was done based on different resolution strategies that were mapped according to CDAR specification. The first part of the technique is focused in identifying the type of conflict in the blocks that arises after partitioning. The second part focuses on the resolution mapping of the conflicts based on the constraints applied depending on the validation and user scenario. RESULTS: We used a publicly available dataset of CDAR documents, identified all conflicted documents and resolved all the them successfully to avoid any semantic loss. In our experiment we tested up to 87,000 CDAR documents and successfully identified the conflicts and resolved the semantic issues. CONCLUSION: We have presented a novel study that focuses on the semantics of big data which did not compromise the performance and resolved the semantic issues risen during the processing of clinical documents.

Use of mind maps and iterative decision trees to develop a guideline-based clinical decision support system for routine surgical practice: case study in thyroid nodules.

OBJECTIVE: The study sought to develop a clinical decision support system (CDSS) for the treatment of thyroid nodules, using a mind map and iterative decision tree (IDT) approach to the integration of clinical practice guidelines (CPGs). MATERIALS AND METHODS: Thyroid nodule CPGs of the American Thyroid Association and Korean Thyroid Association were analyzed by endocrine surgeons (domain experts) and computer scientists. Clinical knowledge from the CPGs was expressed using mind maps. The mind maps were analyzed and converted into IDTs. The final IDT was implemented as a set of candidate rules (3700) for a knowledge-based CDSS. The system was evaluated via a retrospective review of the medical records of 483 patients who had undergone thyroidectomy between January and December 2015 at a single tertiary center (Seoul National University Hospital Bundang, Korea). RESULTS: Concordance between CDSS recommendations and treatment in routine clinical practice was 78.9%. In the 21.1% discordant cases, deviation from the CDSS treatment recommendation was mainly attributable to (1) refusal of the patient to undergo total thyroidectomy and (2) conversion from lobectomy to total thyroidectomy following an unexpected histological finding during intraoperative frozen biopsy lymph node analysis. CONCLUSIONS: The present study demonstrated that a knowledge-based CDSS is feasible in the treatment of thyroid nodules. A high-quality knowledge-based CDSS was developed, and medical domain and computer scientists collaborated effectively in an integrated development environment. The mind map and IDT approach represents a pioneering method of integrating knowledge from CPGs.

Context-aware grading of quality evidences for evidence-based decision-making.

Processing huge repository of medical literature for extracting relevant and high-quality evidences demands efficient evidence support methods. We aim at developing methods to automate the process of finding quality evidences from a plethora of literature documents and grade them according to the context (local condition). We propose a two-level methodology for quality recognition and grading of evidences. First, quality is recognized using quality recognition model; second, context-aware grading of evidences is accomplished. Using 10-fold cross-validation, the proposed quality recognition model achieved an accuracy of 92.14 percent and improved the baseline system accuracy by about 24 percent. The proposed context-aware grading method graded 808 out of 1354 test evidences as highly beneficial for treatment purpose. This infers that around 60 percent evidences shall be given more importance as compared to the other 40 percent evidences. The inclusion of context in recommendation of evidence makes the process of evidence-based decision-making "situation-aware."

Automated ontology generation framework powered by linked biomedical ontologies for disease-drug domain.

OBJECTIVE AND BACKGROUND: The exponential growth of the unstructured data available in biomedical literature, and Electronic Health Record (EHR), requires powerful novel technologies and architectures to unlock the information hidden in the unstructured data. The success of smart healthcare applications such as clinical decision support systems, disease diagnosis systems, and healthcare management systems depends on knowledge that is understandable by machines to interpret and infer new knowledge from it. In this regard, ontological data models are expected to play a vital role to organize, integrate, and make informative inferences with the knowledge implicit in that unstructured data and represent the resultant knowledge in a form that machines can understand. However, constructing such models is challenging because they demand intensive labor, domain experts, and ontology engineers. Such requirements impose a limit on the scale or scope of ontological data models. We present a framework that will allow mitigating the time-intensity to build ontologies and achieve machine interoperability. METHODS: Empowered by linked biomedical ontologies, our proposed novel Automated Ontology Generation Framework consists of five major modules: a) Text Processing using compute on demand approach. b) Medical Semantic Annotation using N-Gram, ontology linking and classification algorithms, c) Relation Extraction using graph method and Syntactic Patterns, d), Semantic Enrichment using RDF mining, e) Domain Inference Engine to build the formal ontology. RESULTS: Quantitative evaluations show 84.78% recall, 53.35% precision, and 67.70% F-measure in terms of disease-drug concepts identification; 85.51% recall, 69.61% precision, and F-measure 76.74% with respect to taxonomic relation extraction; and 77.20% recall, 40.10% precision, and F-measure 52.78% with respect to biomedical non-taxonomic relation extraction. CONCLUSION: We present an automated ontology generation framework that is empowered by Linked Biomedical Ontologies. This framework integrates various natural language processing, semantic enrichment, syntactic pattern, and graph algorithm based techniques. Moreover, it shows that using Linked Biomedical Ontologies enables a promising solution to the problem of automating the process of disease-drug ontology generation.

The intersection of school corporal punishment and associated factors: Baseline results from a randomized controlled trial in Pakistan.

Violence against youth is a global issue; one form of youth victimization is school corporal punishment. We use baseline assessments from a cluster randomized controlled trial to examine the prevalence of school corporal punishment, by gender, and the relationship to levels of peer violence at school, parent corporal punishment, youth food security and youth academic performance and school attendance in Pakistan. Forty homogenous public schools in the urban city of Hyderabad, Pakistan were chosen for randomization into the trial evaluating a youth violence prevention intervention. 1752 6th graders, age 11-14 years, were selected as the target population. Since schools are segregated by gender in Pakistan, data are from interviews in 20 boys' schools and 20 girls' schools. Overall, 91.4% of boys and 60.9% of girls reported corporal punishment at school in the previous 4 weeks and 60.3% of boys had been physically punished at home in the past 4 weeks compared to 37.1% of girls. Structural equation modeling revealed one direct pathway for both boys and girls from food insecurity to corporal punishment at school while indirect pathways were mediated by depression, the number of days missed from school and school performance and for boys also by engagement in peer violence. Exposure to corporal punishment in school and from parents differs by gender, but in both boys and girls poverty in the form of food insecurity was an important risk factor, with the result that poorer children are victimized more by adults.