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Cancer Biology & Therapy Sep 2021Scholarly requirements have led to a massive increase of transcriptomic data in the public domain, with millions of samples available for secondary research. We...
Scholarly requirements have led to a massive increase of transcriptomic data in the public domain, with millions of samples available for secondary research. We identified gene-expression datasets representing 10,214 breast-cancer patients in public databases. We focused on datasets that included patient metadata on race and/or immunohistochemistry (IHC) profiling of the ER, PR, and HER-2 proteins. This review provides a summary of these datasets and describes findings from 32 research articles associated with the datasets. These studies have helped to elucidate relationships between IHC, race, and/or treatment options, as well as relationships between IHC status and the breast-cancer intrinsic subtypes. We have also identified broad themes across the analysis methodologies used in these studies, including breast cancer subtyping, deriving predictive biomarkers, identifying differentially expressed genes, and optimizing data processing. Finally, we discuss limitations of prior work and recommend future directions for reusing these datasets in secondary analyses.
Topics: Biomarkers, Tumor; Breast Neoplasms; Female; Humans; Immunohistochemistry; Receptor, ErbB-2; Receptors, Progesterone; Transcriptome
PubMed: 34412551
DOI: 10.1080/15384047.2021.1953902 -
Therapeutic Advances in Infectious... 2021Chagas disease (CD) is caused by . When acquired, the disease develops in stages. For diagnosis, laboratory confirmation is required, and an extensive assessment of the... (Review)
Review
INTRODUCTION
Chagas disease (CD) is caused by . When acquired, the disease develops in stages. For diagnosis, laboratory confirmation is required, and an extensive assessment of the patient's health should be performed. Treatment consists of the administration of trypanocidal drugs, which may cause severe adverse effects. The objective of our systematic review was to analyze data contained in the CD published case reports to understand the challenges that patients and clinicians face worldwide.
MATERIALS AND METHODS
We performed a systematic review following the PRISMA guidance. PubMed database was explored using the terms 'American trypanosomiasis' or 'Chagas disease'. Results were limited to human case reports written in English or Spanish. A total of 258 reports (322 patients) were included in the analysis. Metadata was obtained from each article. Following this, it was analyzed to obtain descriptive measures.
RESULTS
From the sample, 56.2% were males and 43.8% were females. Most cases were from endemic countries (85.4%). The most common clinical manifestations were fever during the acute stage (70.0%), dyspnea during the chronic stage in its cardiac form (53.7%), and constipation during the chronic stage in its digestive form (73.7%). Most patients were diagnosed in the chronic stage (72.0%). Treatment was administered in 56.2% of cases. The mortality rate for the acute stage cases was 24.4%, while for the chronic stage this was 28.4%.
DISCUSSION
CD is a parasitic disease endemic to Latin America, with increasing importance due to human and vector migration. In this review, we report reasons for delays in diagnosis and treatment, and trends in medical practices. Community awareness must be increased to improve CD's diagnoses; health professionals should be appropriately trained to detect and treat infected individuals. Furthermore, public health policies are needed to increase the availability of screening and diagnostic tools, trypanocidal drugs, and, eventually, vaccines.
PubMed: 34408874
DOI: 10.1177/20499361211033715 -
Journal of Medical Internet Research Jul 2021Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par... (Review)
Review
BACKGROUND
Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical practice, dermatologists also use other patient data beyond the visual aspects present in a digitized image, further increasing their diagnostic accuracy. Several pilot studies have recently investigated the effects of integrating different subtypes of patient data into CNN-based skin cancer classifiers.
OBJECTIVE
This systematic review focuses on the current research investigating the impact of merging information from image features and patient data on the performance of CNN-based skin cancer image classification. This study aims to explore the potential in this field of research by evaluating the types of patient data used, the ways in which the nonimage data are encoded and merged with the image features, and the impact of the integration on the classifier performance.
METHODS
Google Scholar, PubMed, MEDLINE, and ScienceDirect were screened for peer-reviewed studies published in English that dealt with the integration of patient data within a CNN-based skin cancer classification. The search terms skin cancer classification, convolutional neural network(s), deep learning, lesions, melanoma, metadata, clinical information, and patient data were combined.
RESULTS
A total of 11 publications fulfilled the inclusion criteria. All of them reported an overall improvement in different skin lesion classification tasks with patient data integration. The most commonly used patient data were age, sex, and lesion location. The patient data were mostly one-hot encoded. There were differences in the complexity that the encoded patient data were processed with regarding deep learning methods before and after fusing them with the image features for a combined classifier.
CONCLUSIONS
This study indicates the potential benefits of integrating patient data into CNN-based diagnostic algorithms. However, how exactly the individual patient data enhance classification performance, especially in the case of multiclass classification problems, is still unclear. Moreover, a substantial fraction of patient data used by dermatologists remains to be analyzed in the context of CNN-based skin cancer classification. Further exploratory analyses in this promising field may optimize patient data integration into CNN-based skin cancer diagnostics for patients' benefits.
Topics: Dermoscopy; Humans; Melanoma; Neural Networks, Computer; Skin Neoplasms
PubMed: 34255646
DOI: 10.2196/20708 -
BMC Medical Informatics and Decision... Jun 2021Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology...
BACKGROUND
Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to radiology is of significance but recent reviews on this are limited. This study systematically assesses and quantifies recent literature in NLP applied to radiology reports.
METHODS
We conduct an automated literature search yielding 4836 results using automated filtering, metadata enriching steps and citation search combined with manual review. Our analysis is based on 21 variables including radiology characteristics, NLP methodology, performance, study, and clinical application characteristics.
RESULTS
We present a comprehensive analysis of the 164 publications retrieved with publications in 2019 almost triple those in 2015. Each publication is categorised into one of 6 clinical application categories. Deep learning use increases in the period but conventional machine learning approaches are still prevalent. Deep learning remains challenged when data is scarce and there is little evidence of adoption into clinical practice. Despite 17% of studies reporting greater than 0.85 F1 scores, it is hard to comparatively evaluate these approaches given that most of them use different datasets. Only 14 studies made their data and 15 their code available with 10 externally validating results.
CONCLUSIONS
Automated understanding of clinical narratives of the radiology reports has the potential to enhance the healthcare process and we show that research in this field continues to grow. Reproducibility and explainability of models are important if the domain is to move applications into clinical use. More could be done to share code enabling validation of methods on different institutional data and to reduce heterogeneity in reporting of study properties allowing inter-study comparisons. Our results have significance for researchers in the field providing a systematic synthesis of existing work to build on, identify gaps, opportunities for collaboration and avoid duplication.
Topics: Humans; Machine Learning; Natural Language Processing; Radiology; Radiology Information Systems; Reproducibility of Results
PubMed: 34082729
DOI: 10.1186/s12911-021-01533-7 -
Plants (Basel, Switzerland) Apr 2021The early life-history stages of plants, such as germination and seedling establishment, depend on favorable environmental conditions. Changes in the environment at high... (Review)
Review
The early life-history stages of plants, such as germination and seedling establishment, depend on favorable environmental conditions. Changes in the environment at high altitude and high latitude regions, as a consequence of climate change, will significantly affect these life stages and may have profound effects on species recruitment and survival. Here, we synthesize the current knowledge of climate change effects on treeline, tundra, and alpine plants' early life-history stages. We systematically searched the available literature on this subject up until February 2020 and recovered 835 potential articles that matched our search terms. From these, we found 39 studies that matched our selection criteria. We characterized the studies within our review and performed a qualitative and quantitative analysis of the extracted meta-data regarding the climatic effects likely to change in these regions, including projected warming, early snowmelt, changes in precipitation, nutrient availability and their effects on seed maturation, seed dormancy, germination, seedling emergence and seedling establishment. Although the studies showed high variability in their methods and studied species, the qualitative and quantitative analysis of the extracted data allowed us to detect existing patterns and knowledge gaps. For example, warming temperatures seemed to favor all studied life stages except seedling establishment, a decrease in precipitation had a strong negative effect on seed stages and, surprisingly, early snowmelt had a neutral effect on seed dormancy and germination but a positive effect on seedling establishment. For some of the studied life stages, data within the literature were too limited to identify a precise effect. There is still a need for investigations that increase our understanding of the climate change impacts on high altitude and high latitude plants' reproductive processes, as this is crucial for plant conservation and evidence-based management of these environments. Finally, we make recommendations for further research based on the identified knowledge gaps.
PubMed: 33919792
DOI: 10.3390/plants10040768 -
Gut Microbes 2021Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization. This study...
Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization. This study aimed to review the perinatal, physiological, pharmacological, dietary, and environmental factors associated with gut microbiota of PT infants. A total of 587 articles were retrieved from a search of multiple databases. Sixty studies were included in the review after removing duplicates and articles that did not meet the inclusion criteria. Review of this literature revealed that evidence converged on the effect of postnatal age, mode of delivery, use of antibiotics, and consumption of human milk in the composition of gut microbiota of PT infants. Less evidence was found for associations with race, sex, use of different fortifiers, macronutrients, and other medications. Future studies with rich metadata are needed to further explore the impact of the PT exposome on the development of the microbiota in this high-risk population.
Topics: Anti-Bacterial Agents; Diet; Female; Gastrointestinal Microbiome; Gestational Age; Humans; Infant; Infant Formula; Infant, Newborn; Infant, Premature; Male; Milk, Human; Pregnancy; Pregnancy Complications
PubMed: 33818293
DOI: 10.1080/19490976.2021.1884514 -
Briefings in Bioinformatics Mar 2021This study aims at reviewing novel coronavirus disease (COVID-19) datasets extracted from PubMed Central articles, thus providing quantitative analysis to answer...
OBJECTIVE
This study aims at reviewing novel coronavirus disease (COVID-19) datasets extracted from PubMed Central articles, thus providing quantitative analysis to answer questions related to dataset contents, accessibility and citations.
METHODS
We downloaded COVID-19-related full-text articles published until 31 May 2020 from PubMed Central. Dataset URL links mentioned in full-text articles were extracted, and each dataset was manually reviewed to provide information on 10 variables: (1) type of the dataset, (2) geographic region where the data were collected, (3) whether the dataset was immediately downloadable, (4) format of the dataset files, (5) where the dataset was hosted, (6) whether the dataset was updated regularly, (7) the type of license used, (8) whether the metadata were explicitly provided, (9) whether there was a PubMed Central paper describing the dataset and (10) the number of times the dataset was cited by PubMed Central articles. Descriptive statistics about these seven variables were reported for all extracted datasets.
RESULTS
We found that 28.5% of 12 324 COVID-19 full-text articles in PubMed Central provided at least one dataset link. In total, 128 unique dataset links were mentioned in 12 324 COVID-19 full text articles in PubMed Central. Further analysis showed that epidemiological datasets accounted for the largest portion (53.9%) in the dataset collection, and most datasets (84.4%) were available for immediate download. GitHub was the most popular repository for hosting COVID-19 datasets. CSV, XLSX and JSON were the most popular data formats. Additionally, citation patterns of COVID-19 datasets varied depending on specific datasets.
CONCLUSION
PubMed Central articles are an important source of COVID-19 datasets, but there is significant heterogeneity in the way these datasets are mentioned, shared, updated and cited.
Topics: COVID-19; Datasets as Topic; Humans; Information Dissemination; PubMed; SARS-CoV-2
PubMed: 33757278
DOI: 10.1093/bib/bbaa331 -
Open Research Europe 2021The use of advanced algorithmic techniques is increasingly changing the nature of work for highly trained professionals. In the media industry, one of the technical...
The use of advanced algorithmic techniques is increasingly changing the nature of work for highly trained professionals. In the media industry, one of the technical advancements that often comes under the spotlight is automated journalism, a solution generally understood as the auto generation of journalistic stories through software and algorithms, without any human input except for the initial programming. In order to conduct a systematic review of existing empirical research on automated journalism, I analysed a range of variables that can account for the semantical, chronological and geographical features of a selection of academic articles as well as their research methods, theoretical backgrounds and fields of inquiry. I then engaged with and critically assessed the meta-data that I obtained to provide researchers with a good understanding of the main debates dominating the field. My findings suggest that the expression "automated journalism" should be called into question, that more attention should be devoted to non-English speaking scholarship, that the collective and individual impacts of the technology on media practitioners should be better documented and that well-established sociological theories such as institutionalism and Bourdieu's field theory could constitute two adequate frameworks to study automated journalism practices. This systematic literature therefore provides researchers with an overview of the main challenges and debates that are occurring within the field of automated journalism studies. Future studies should, in particular, make use of institutionalism and field theory to explore how automated journalism is impacting the work of media practitioners, which could help unearth common patterns across media organisations.
PubMed: 37645115
DOI: 10.12688/openreseurope.13096.1 -
Environment International Jun 2021Conservation activities and natural resource management interventions have often aimed to tackle the dual challenge of improving nature conservation and human... (Review)
Review
What is the evidence documenting the effects of marine or coastal nature conservation or natural resource management activities on human well-being in South East Asia? A systematic map.
BACKGROUND
Conservation activities and natural resource management interventions have often aimed to tackle the dual challenge of improving nature conservation and human well-being. However, there is concern over the extent to which this dual goal has been achieved, and an increasing recognition of trade-offs and synergies within and between aspects of each of the goals. The amount and scope of the available evidence on the success of conservation and management interventions in both arenas has lacked documentation, for a number of reasons, including limited resources for monitoring and evaluation and the difficulty in bringing together a disparate evidence base. This systematic map focuses on the interaction between marine conservation management and the health and well-being of coastal communities in South East Asia.
METHOD
We searched bibliographic databases to find published literature, and identified grey literature through institutional and organisational website searches and key stakeholders. Eligibility criteria were applied in two stages, title and abstract and full text, with consistency checks. We extracted meta-data on the design and characteristics of each study, from which we produced an interactive database and map, and a narrative summary.
RESULTS
We assessed 42,894 records at title and abstract from the main searches. 1,331 articles were assessed at full text (30 articles were not retrievable). 287 articles (281 studies) were included in the systematic map. Most studies were peer-reviewed publications (90%), and from the Philippines and Indonesia (72%). 31% of studies were solely qualitative, 45% were solely quantitative and 24% included both qualitative and quantitative research. Only 24% (31/127) of quantitative studies included a comparator. We identified knowledge clusters where studies investigated the links between the marine conservation interventions: Site Protection, Economic or Livelihood Incentives or Alternatives, or Habitat Management, and the human health and well-being outcomes: Economic Living Standards, Governance and Empowerment, or Social Relations. In addition, qualitative research clusters were identified exploring the links between the intervention Habitat Management, and the outcome Governance and Empowerment, and between the intervention Economic or Livelihood Incentives or Alternatives, and the outcomes of Governance and Empowerment, and Social Relations. We identified major knowledge gaps in evidence for the effect of marine conservation interventions on the outcomes Freedom of Choice and Action, Security and Safety, Subjective Well-being, Health, and Culture and Spirituality. There was a lack of studies involving Education, Awareness and Activism interventions that reported any human health and well-being outcomes.
CONCLUSION
We present the first updatable, interrogable and comprehensive evidence map on this topic for South East Asia. Our work supports further, detailed investigation of knowledge clusters using systematic review and also serves to identify understudied topic areas. The lack of comparative, quantitative studies suggests that future research should include counterfactuals to strengthen the robustness of evidence base. Users of this systematic map should recognise that much evidence may be national or locally specific, and that we did not undertake an assessment of study quality. Thus, when considering implications for policy and decision-making, users should carefully consider the heterogeneity of available evidence and refer to original research articles to gain a full depth of understanding and context.
Topics: Conservation of Natural Resources; Asia, Eastern; Humans; Natural Resources; Philippines; Socioeconomic Factors
PubMed: 33713939
DOI: 10.1016/j.envint.2021.106397 -
Stroke Research and Treatment 2021This review aimed at figuring out the risk factors of uncontrolled hypertension in stroke. (Review)
Review
OBJECTIVE
This review aimed at figuring out the risk factors of uncontrolled hypertension in stroke.
METHOD
This study systematically analyzed the hypertension risk factors available in the ProQuest, EBSCO, and PubMed databases published between 2010 and December 2019. The risk factors' pooled odds ratio (POR) included in this research was calculated using both fixed and random-effect models. The meta-data analysis was processed using the Review Manager 5.3 (Rev Man 5.3).
RESULT
Of 1868 articles, seven studies were included in this review searched using specific keywords. Based on the analysis results, there were 7 risk factors of uncontrolled hypertension in stroke: medication nonadherence (POR = 2.23 [95% CI 1.71-2.89], = 0.342; = 6.7%), use of antihypertensive drugs (POR = 1.13 [95% CI 1.19-1.59, = 0.001; = 90.9%), stage of hypertension (POR = 1.14 [95% CI 1.02-1.27], = <0.001; = 97.1%), diabetes mellitus (POR = 0.71 [95% CI 0.52-0.99], = <0.001; = 96.5%), atrial fibrillation (POR = 1.74 [95% CI 1.48-2.04)], = <0.001; = 93.1%), triglycerides (POR = 1.47 [95% CI 1.23-1.75], = 0.879; = 0%), and age (POR = 1.03 [95% CI 0.89-1.18], = <0.001; = 97.5%]. There were no bias publications among studies. Medication nonadherence and triglycerides had homogeneous variations, while the others had heterogeneous variations.
CONCLUSION
Medication nonadherence, triglycerides, stage of hypertension, atrial fibrillation, and use of antihypertensive drugs significantly affect the uncontrolled hypertension in stroke.
PubMed: 33680423
DOI: 10.1155/2021/6683256