Consumer behavior towards new energy vehicles: Developing a theoretical framework.

New energy vehicles (NEVs), owing to their low carbon emission, have gained immense importance to achieve the net-zero emission target. The global NEVs market has grown significantly over the last decade. China, the United States (US), and Europe are the leading markets for NEVs. This study systematically and critically reviews NEV literature on consumer behavior pertaining to NEV adoption. An attempt is made to uncover the current research trends, research settings, theoretical perspectives, and key factors influencing consumer behavior towards NEVs. These factors are further categorized into five broad factors: (a) economic factors, (b) policy and regulatory factors, (c) psychological factors, (d) infrastructural and technological factors, and (e) demographic factors. Through a critical analysis of existing theories, this study delineates the complex phenomenon of consumer behavior towards NEV adoption, offering a holistic understanding of the key factors influencing consumer behavior. This review suggests that purchasing price, charging infrastructures, consumers' attitudes towards the environment, and government policies are decisive to NEV adoption. This study contributes to the NEV adoption literature by proposing an integrated theoretical framework. Further, it outlines the managerial and policy implications for transitioning towards NEVs to achieve net-zero emission targets.

Biology, ecology, and epidemiology of Alternaria species affecting tomato: ground information for the development of a predictive model.

Among pathogens that affect tomato, Alternaria spp. are important due to their implications in yield losses and the contamination of tomato products by mycotoxins. In this study, a systematic literature review was conducted to retrieve and analyze available data on the Alternaria-tomato pathosystem, with particular attention focused on the main biological processes included in the pathogen life cycle and mycotoxin production. We considered 110 papers (selected from initial 2,138 papers) on five Alternaria species that were historically related or recently identified to cause damage to tomato leafage and fruits. Published mathematical models related to Alternaria diseases in tomato were also screened based on their aim and development methods, highlighting the wide use of empirical approach. Retrieved information was also evaluated for applications in building a mechanistic, weather-driven model that incorporates the key steps of the pathogen life cycle. This systematic review highlights several knowledge gaps, including the effect of wetness on infection and environmental requirements for mycotoxin production, and suggests paths for further research especially for recently isolated species.

A systematic review of economic evaluations of orphan medicines for the management of spinal muscular atrophy.

Spinal muscular atrophy (SMA) is a rare inherited autosomal recessive progressive disease of a varying phenotype, with varying clinical symptoms, and as a result the patients suffering from it require multiple types of care. It was deemed useful to conduct a systematic literature review on the pharmacoeconomic evaluations of all currently registered disease-modifying therapies in order to inform policy and highlight research gaps. Pharmacoeconomic analyses written in English and published after 2016 were considered for inclusion. PubMed/Medline, Global Health and Embase were systematically and separately searched between 16 October and 23 October 2023. Hand-searching was also conducted on PubMed based on reference lists of published literature. After the exclusion criteria were applied, 14 studies were included. BMJ checklist was used for quality assessment and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist was used to assess the quality of reporting of all included studies. Data extraction was performed manually. Regarding evidence synthesis, data were heterogeneous and are thus presented based on comparison. This study confirms the need for pharmacoeconomic analyses (cost-effectiveness or cost-utility) also in cases when the cost of treatment is very high and the incremental cost-effectiveness ratio values exceed the usual, acceptable values for standard therapy. Specific willingness to pay thresholds for orphan medicines are of the utmost importance, to allow patients with SMA to have access to safe and effective treatments. With such economic evaluations, it is possible to compare the value of medications with the same indication, but it should be emphasized that in the interpretation of data and in making decisions about the use of medicines, the impact of new knowledge should be considered.

Brain volume loss in relapsing multiple sclerosis: indirect treatment comparisons of available disease-modifying therapies.

BACKGROUND: Brain volume loss (BVL) has been identified as a predictor of disability progression in relapsing multiple sclerosis (RMS). As many available disease-modifying treatments (DMTs) have shown an effect on slowing BVL, this is becoming an emerging clinical endpoint in RMS clinical trials. METHODS: In this study, a systematic literature review was conducted to identify BVL results from randomized controlled trials of DMTs in RMS. Indirect treatment comparisons (ITCs) were conducted to estimate the relative efficacy of DMTs on BVL using two approaches: a model-based meta-analysis (MBMA) with adjustment for measurement timepoint and DMT dosage, and a network meta-analysis (NMA). RESULTS: In the MBMA, DMTs associated with significantly reduced BVL versus placebo at two years included fingolimod (mean difference [MD] = 0.25; 95% confidence interval [CI] = 0.15 - 0.36), ozanimod (MD = 0.26; 95% CI = 0.12 - 0.41), teriflunomide (MD = 0.38; 95% CI = 0.20 - 0.55), alemtuzumab (MD = 0.38; 95% CI = 0.10 - 0.67) and ponesimod (MD = 0.71; 95% CI = 0.48 - 0.95), whereas interferons and natalizumab performed the most poorly. The results of NMA analysis were generally comparable with those of the MBMA. CONCLUSIONS: Limitations of these analyses included the potential for confounding due to pseudoatrophy, and a lack of long-term clinical data for BVL. Our findings suggest that important differences in BVL may exist between DMTs. Continued investigation of BVL in studies of RMS is important to complement traditional disability endpoints, and to foster a better understanding of the mechanisms by which DMTs can slow BVL.

Is interval chemotherapy safe and does it improve the outcome of patients with colorectal liver metastases undergoing multimodal two-stage hepatectomy? - A systematic literature review.

BACKGROUND: Multimodal two-stage hepatectomy (mTSH) is used in patients with bilobar colorectal liver metastases (CRLM) that cannot be treated with one surgical procedure due to insufficient future liver remnant. Interval chemotherapy has been proposed to improve disease control in CRLM patients undergoing mTSH. We here present a narrative review of clinical studies on mTSH including the use of interval chemotherapy in patients with CRLM. METHODS: A systematic literature search of the PubMed databases as well as the ClinicalTrials.gov registry was performed. RESULTS: The use of interval chemotherapy during mTSH was reported in 23 studies and applied in 595 out of 1,461 patients with CRLM. Two studies report on the actual effects of this treatment, one study describes a trend towards improved disease progression rate. No serious adverse events caused by interval chemotherapy were observed. There is currently no randomized clinical trial investigating the efficacy and safety of interval chemotherapy during mTSH. CONCLUSION: The currently available data indicate that interval chemotherapy does neither impair liver hypertrophy during mTSH nor cause procedure-associated complications in patients with CRLM. Results from randomized clinical trials on the potential positive effect on disease control are not yet available.

Clinical Decision Support and Natural Language Processing in Medicine: Systematic Literature Review.

BACKGROUND: Ensuring access to accurate and verified information is essential for effective patient treatment and diagnosis. Although health workers rely on the internet for clinical data, there is a need for a more streamlined approach. OBJECTIVE: This systematic review aims to assess the current state of artificial intelligence (AI) and natural language processing (NLP) techniques in health care to identify their potential use in electronic health records and automated information searches. METHODS: A search was conducted in the PubMed, Embase, ScienceDirect, Scopus, and Web of Science online databases for articles published between January 2000 and April 2023. The only inclusion criteria were (1) original research articles and studies on the application of AI-based medical clinical decision support using NLP techniques and (2) publications in English. A Critical Appraisal Skills Programme tool was used to assess the quality of the studies. RESULTS: The search yielded 707 articles, from which 26 studies were included (24 original articles and 2 systematic reviews). Of the evaluated articles, 21 (81%) explained the use of NLP as a source of data collection, 18 (69%) used electronic health records as a data source, and a further 8 (31%) were based on clinical data. Only 5 (19%) of the articles showed the use of combined strategies for NLP to obtain clinical data. In total, 16 (62%) articles presented stand-alone data review algorithms. Other studies (n=9, 35%) showed that the clinical decision support system alternative was also a way of displaying the information obtained for immediate clinical use. CONCLUSIONS: The use of NLP engines can effectively improve clinical decision systems' accuracy, while biphasic tools combining AI algorithms and human criteria may optimize clinical diagnosis and treatment flows. TRIAL REGISTRATION: PROSPERO CRD42022373386; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=373386.

The role of cardiac acoustic biomarkers in monitoring patients with heart failure: A systematic literature review.

Heart failure (HF) creates a considerable clinical, humanistic and economic burden on patients and caregivers as well as on healthcare systems. To attenuate the significant burden of HF, there is a need for enhanced management of patients with HF. The use of digital tools for remote non-invasive monitoring of heart parameters is gaining traction, and cardiac acoustic biomarkers (CABs) have been proposed as a complementary set of measures to assess heart function alongside traditional methods such as electrocardiogram and echocardiography. We conducted a systematic literature review to evaluate associations between CABs and HF outcomes. Embase and MEDLINE databases were searched for recent studies published between 2013 and 2023 that evaluated CABs in patients with HF. Additional grey literature (i.e., conference, congress and pre-print publications from January 2021 to May 2023) searches were included. Two reviewers independently examined all articles; a third resolved conflicts. Data were extracted from articles meeting inclusion criteria. Extracted studies underwent quality and bias assessments using the Joanna Briggs Institute (JBI) critical appraisal tools. In total, 3074 records were screened, 73 full-text articles were assessed for eligibility and 27 publications were included. Third heart sound (S3) and electromechanical activation time (EMAT) were the CABs most often reported in the literature for monitoring HF. Fifteen publications discussed changes in S3 characteristics and its role in HF detection or outcomes: six studies highlighted S3 assessment among various groups of patients with HF; four studies evaluated the strength or amplitude of S3 with clinical outcomes; five studies assessed the relationship between S3 presence and clinical outcomes; and one study assessed both S3 presence and amplitude in relation to HF clinical outcomes. Eleven publications reported on EMAT and its derivatives: five studies on the relationship between EMAT and HF and six studies on the association of EMAT and HF clinical outcomes. Studies reporting the first and fourth heart sound, left ventricular ejection time and systolic dysfunction index were limited. Published literature supported S3 and EMAT as robust CAB measures in HF that may have value in remote clinical monitoring and management of patients with HF. Additional studies designed to test the predictive power of these CABs, and others less well-characterized, are needed. This work was funded by Astellas Pharma Inc.

Systematic literature review of the indirect costs and humanistic burden of ß-thalassemia.

Background: ß-Thalassemia is an inherited blood disorder requiring lifetime management of anemia and its complications. Objective: This study aimed to determine the indirect costs and humanistic burden of ß-thalassemia. Design: A systematic literature review was conducted. Data sources and methods: Searches were conducted in Embase, MEDLINE, MEDLINE In-Process, and EconLit (November 1, 2010, to November 25, 2020). Studies reporting indirect costs and health-related quality of life (HRQoL) for patients with ß-thalassemia were eligible. Results: Seventy-five publications were included. Mean annual days lost due to transfusion-related absenteeism ranged from 15.6 to 35 days. Patients spent a mean of 592 min (standard deviation (SD): 349) daily on disease management on transfusion days and 91 min (SD: 221) daily on non-transfusion days. Patients with non-transfusion-dependent ß-thalassemia (NTDT) showed worse HRQoL versus those with transfusion-dependent ß-thalassemia (TDT) on the 36-item Short Form Health Survey (75.8 vs 66.5; p = 0.021). Caregivers of patients with TDT had more severe stress compared with patients (20.17 vs 18.95; p = 0.006), as measured by the standardized Cohen Perceived Stress Questionnaire. Conclusion: TDT is associated with substantial indirect costs and caregiver burden, and NTDT is associated with worse HRQoL. There is an unmet need for novel treatments in both TDT and NTDT that minimize patient and caregiver burden.

The NICE search filters for treating and managing COVID-19: validation in MEDLINE and Embase (Ovid).

Objective: In this paper we report how the United Kingdom's National Institute for Health and Care Excellence (NICE) search filters for treating and managing COVID-19 were validated for use in MEDLINE (Ovid) and Embase (Ovid). The objective was to achieve at least 98.9% for recall and 64% for precision. Methods: We did two tests of recall to finalize the draft search filters. We updated the data from an earlier peer-reviewed publication for the first recall test. For the second test, we collated a set of systematic reviews from Epistemonikos COVID-19 L.OVE and extracted their primary studies. We calculated precision by screening all the results retrieved by the draft search filters from a targeted sample covering 2020-23. We developed a gold-standard set to validate the search filter by using all articles available from the "Treatment and Management" subject filter in the Cochrane COVID-19 Study Register. Results: In the first recall test, both filters had 99.5% recall. In the second test, recall was 99.7% and 99.8% in MEDLINE and Embase respectively. Precision was 91.1% in a deduplicated sample of records. In validation, we found the MEDLINE filter had recall of 99.86% of the 14,625 records in the gold-standard set. The Embase filter had 99.88% recall of 19,371 records. Conclusion: We have validated search filters to identify records on treating and managing COVID-19. The filters may require subsequent updates, if new SARS-CoV-2 variants of concern or interest are discussed in future literature.

A systematic literature review and future research agenda to study consumer acceptance of novel foods and beverages.

In response to the rising global demand for healthier and more sustainable food resources, novel and unconventional food and beverages are being developed and incorporated into our diets. However, existing literature provides a limited understanding of consumers' acceptance of these innovations. This study undertakes a systematic literature review to examine the dynamics between consumers and novel foods and beverages. The objectives are to uncover the factors that influence consumer choices of these products, identify future research needs, and contribute to the development of effective marketing strategies for novel food and beverage adoption. This systematic review analyses 99 research papers, selected from an initial pool of 4,280, sourced from Scopus and Web of Science databases. The papers were published between 2011 and 2023 in journals listed by Australian Business Deans Council and classified as Q1 in the SJR journal ranking. The articles have been reviewed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol and TCCM (Theory, Context, Characteristics and Methodology) framework. The findings highlight a reliance on data-driven methods and suggest that integrating relevant theories could enhance future research outcomes. Most studies focused on the acceptance of technology-based innovations in developed countries, indicating a need to explore novel foods and beverages in developing regions. Consumer-related factors, especially psychological aspects, were the primary focus, suggesting opportunities to investigate additional variables, such as product-related and situational factors, that influence acceptance. Finally, the predominance of quantitative research indicates a potential benefit in incorporating qualitative and multi-method approaches to gain deeper insights into consumer attitudes and motivations.

Applications of genome-scale metabolic models to the study of human diseases: A systematic review.

BACKGROUND AND OBJECTIVES: Genome-scale metabolic networks (GEMs) represent a valuable modeling and computational tool in the broad field of systems biology. Their ability to integrate constraints and high-throughput biological data enables the study of intricate metabolic aspects and processes of different cell types and conditions. The past decade has witnessed an increasing number and variety of applications of GEMs for the study of human diseases, along with a huge effort aimed at the reconstruction, integration and analysis of a high number of organisms. This paper presents a systematic review of the scientific literature, to pursue several important questions about the application of constraint-based modeling in the investigation of human diseases. Hopefully, this paper will provide a useful reference for researchers interested in the application of modeling and computational tools for the investigation of metabolic-related human diseases. METHODS: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Elsevier Scopus®, National Library of Medicine PubMed® and Clarivate Web of Science™ databases were enquired, resulting in 566 scientific articles. After applying exclusion and eligibility criteria, a total of 169 papers were selected and individually examined. RESULTS: The reviewed papers offer a thorough and up-to-date picture of the latest modeling and computational approaches, based on genome-scale metabolic models, that can be leveraged for the investigation of a large variety of human diseases. The numerous studies have been categorized according to the clinical research area involved in the examined disease. Furthermore, the paper discusses the most typical approaches employed to derive clinically-relevant information using the computational models. CONCLUSIONS: The number of scientific papers, utilizing GEM-based approaches for the investigation of human diseases, suggests an increasing interest in these types of approaches; hopefully, the present review will represent a useful reference for scientists interested in applying computational modeling approaches to investigate the aetiopathology of human diseases; we also hope that this work will foster the development of novel applications and methods for the discovery of clinically-relevant insights on metabolic-related diseases.

Smart, sustainable, and circular port maintenance: A comprehensive framework and multi-stakeholder approach.

Ports and waterways are key in supporting the waterborne supply chains that form the backbone of global trade. Maintaining adequate water depth is vital for accessibility and safe navigation. Port authorities and contractors are the key players in developing maintenance strategies, and they strive for a mutually beneficial compromise. Port authorities aim to optimize port performance while keeping costs and delays at acceptable levels. Contractors aim to optimize the use of equipment and execution strategies to achieve cost-effectiveness and time efficiency. While minimum cost and duration are common and simple decision criteria, there is growing societal pressure to incorporate smart, sustainable, and circular elements. However, these elements are less straightforward to interpret and there is a lack of a comprehensive framework to quantify smart, circular, and sustainable strategies. This lack of clarity presents significant challenges in balancing traditional and emerging objectives in port maintenance. Our study directly addresses this gap by providing a structured approach to decision-making that integrates these critical but complex elements. As a result, trade-offs on these important issues are harder to achieve reducing the contributions of port authorities and contractors. This study addresses this gap by applying the Frame of Reference (FoR) method to extract objectives and indicators for decision-making from both the port authorities' and contractors' perspectives. We fill in the prescribed elements of the basic FoR template through a systematic literature review (SLR), clarifying to what extent consensus exists on these topics. The SLR revealed 128 articles and identified common strategies, research methods, influential journals, and contributing countries. Projecting these findings onto the basic FoR template showed that the protection of marine ecosystems and sediment management has received considerable attention from researchers while mitigating emissions and adopting smart techniques are emerging subjects in the literature that need further investigations. As a result, this study offers theoretical and managerial insights to improve what can be achieved with smart, circular, and sustainable maintenance strategies, while identifying crucial remaining knowledge gaps.

Gonadal Mosaicism as a Rare Inheritance Pattern in Recessive Genodermatoses: Report of Two Cases with Pseudoxanthoma Elasticum and Literature Review.

Germline mosaicism in autosomal recessive disorders is considered a rare disease mechanism with important consequences for diagnosis and patient counseling. In this report, we present two families with PXE in which paternal germline mosaicism for an ABCC6 whole-gene deletion was observed. The first family further illustrates the clinical challenges in PXE, with a typical PXE retinopathy in an apparently heterozygous carrier parent. A systematic review of the literature on gonadal mosaicism in autosomal recessive genodermatoses revealed 16 additional patients. As in most reported families, segregation analysis data are not mentioned, and this may still be an underrepresentation. Though rare, the possibility of germline mosaicism emphasizes the need for variant verification in parents and sibs of a newly diagnosed proband, as it has significant implications for genetic counseling and management.

When we talk about Big Data, What do we really mean? Toward a more precise definition of Big Data.

Despite the lack of consensus on an official definition of Big Data, research and studies have continued to progress based on this "no consensus" stance over the years. However, the lack of a clear definition and scope for Big Data results in scientific research and communication lacking a common ground. Even with the popular "V" characteristics, Big Data remains elusive. The term is broad and is used differently in research, often referring to entirely different concepts, which is rarely stated explicitly in papers. While many studies and reviews attempt to draw a comprehensive understanding of Big Data, there has been little systematic research on the position and practical implications of the term Big Data in research environments. To address this gap, this paper presents a Systematic Literature Review (SLR) on secondary studies to provide a comprehensive overview of how Big Data is used and understood across different scientific domains. Our objective was to monitor the application of the Big Data concept in science, identify which technologies are prevalent in which fields, and investigate the discrepancies between the theoretical understanding and practical usage of the term. Our study found that various Big Data technologies are being used in different scientific fields, including machine learning algorithms, distributed computing frameworks, and other tools. These manifestations of Big Data can be classified into four major categories: abstract concepts, large datasets, machine learning techniques, and the Big Data ecosystem. This study revealed that despite the general agreement on the "V" characteristics, researchers in different scientific fields have varied implicit understandings of Big Data. These implicit understandings significantly influence the content and discussions of studies involving Big Data, although they are often not explicitly stated. We call for a clearer articulation of the meaning of Big Data in research to facilitate smoother scientific communication.

Patient-reported preferences for subcutaneous or intravenous administration of parenteral drug treatments in adults with immune disorders: a systematic review and meta-analysis.

Aim: Several studies have found subcutaneous (SC) and intravenous (IV) administration of similar drugs for long-lasting immunological and autoimmune diseases to have similar clinical effectiveness, meaning that what patients report they prefer is, or should be, a major factor in treatment choices. Therefore, it is important to systematically compile evidence regarding patient preferences, treatment satisfaction and health-related quality of life (HRQL) using SC or IV administration of the same drug. Materials & methods: PubMed database searches were run on 15 October 2021. Studies involving patients with experience of both home-based SC and hospital-based IV administration of immunoglobulins or biological therapies for the treatment of any autoimmune disease or primary immunodeficiencies (PIDs) were included. The outcomes assessed were patient preferences, treatment satisfaction and HRQL. Preference data were meta-analyzed using a random-effects model. Results: In total, 3504 citations were screened, and 46 publications describing 37 studies were included in the review. There was a strong overall preference for SC over IV administration, with similar results seen for PIDs and autoimmune diseases: PID, 80% (95% confidence interval [CI], 64-94%) preferred SC; autoimmune diseases, 83% (95% CI: 73-92%); overall, 82% (95% CI: 75-89%). The meta-analysis also found that 84% (95% CI: 75-92%) of patients preferred administration at home to treatment in hospital. Analysis of treatment satisfaction using the life quality index found consistently better treatment interference and treatment setting scores with SC administration than with IV administration. Conclusion: Compared with IV infusions in hospital, patients tend to prefer, to be more satisfied with and to report better HRQL with SC administration of the same drug at home, primarily due to the greater convenience. This study contributes to evidence-based care of patients with autoimmune diseases or PIDs.

Understanding Users' Acceptance of Artificial Intelligence Applications: A Literature Review.

In recent years, with the continuous expansion of artificial intelligence (AI) application forms and fields, users' acceptance of AI applications has attracted increasing attention from scholars and business practitioners. Although extant studies have extensively explored user acceptance of different AI applications, there is still a lack of understanding of the roles played by different AI applications in human-AI interaction, which may limit the understanding of inconsistent findings about user acceptance of AI. This study addresses this issue by conducting a systematic literature review on AI acceptance research in leading journals of Information Systems and Marketing disciplines from 2020 to 2023. Based on a review of 80 papers, this study made contributions by (i) providing an overview of methodologies and theoretical frameworks utilized in AI acceptance research; (ii) summarizing the key factors, potential mechanisms, and theorization of users' acceptance response to AI service providers and AI task substitutes, respectively; and (iii) proposing opinions on the limitations of extant research and providing guidance for future research.

Caregiver Burden among Patients with Influenza or Influenza-like Illness (ILI): A Systematic Literature Review.

Influenza and influenza-like illness (ILI) pose significant clinical and economic burdens globally each year. This systematic literature review examined quantitative studies evaluating the impact of patients' influenza/ILI on their caregivers' well-being, focusing on health-related quality of life (HRQoL), work productivity, and activity impairment. A comprehensive search across six databases, including the Cochrane Database of Systematic Reviews, Embase, MEDLINE via PubMed, Ovid, PsycNet, and Web of Science, yielded 18,689 records, of which 13,156 abstracts were screened, and 662 full-text articles were reviewed from January 2007 to April 2024. Thirty-six studies [HRQoL: 2; productivity: 33; both: 1] covering 22 countries were included. Caregivers of 47,758 influenza or ILI patients across 123 study cohorts were assessed in the review. The mean workday loss among caregivers ranged from 0.5 to 10.7 days per episode, influenced by patients' influenza status (positive or negative), disease severity (mild or moderate-to-severe), age, viral type (influenza A or B), and vaccination/treatment usage. The HRQoL of caregivers, including their physical and emotional well-being, was affected by a patient's influenza or ILI, where the severity and duration of a patient's illness were associated with worse HRQoL. This review shows that the consequences of influenza or ILI significantly affect not only patients but also their caregivers.

Standardization of coding definitions for sickle cell disease complications: A systematic literature review.

PURPOSE: Sickle cell disease (SCD) affects all organ systems and is characterized by numerous acute and chronic complications and comorbidities. Standardized codes are needed for complications/comorbidities used in real-world evidence (RWE) studies that rely on administrative and medical coding. This systematic literature review was conducted to produce a comprehensive list of complications/comorbidities associated with SCD, along with their diagnosis codes used in RWE studies. METHODS: A search in MEDLINE and Embase identified studies published from 2016 to 2023. Studies were included if they were conducted in US SCD populations and reported complications/comorbidities and respective International Classification of Diseases, Clinical Modification (ICD-CM) codes. All identified complications/comorbidities and codes were reviewed by a certified medical coding expert and hematologist. RESULTS: Of 1851 identified studies, 39 studies were included. The most reported complications/comorbidities were stroke, acute chest syndrome, pulmonary embolism, venous thromboembolism, and vaso-occlusive crisis. Most of the studies used ICD-9-CM codes (n = 21), while some studies used ICD-10-CM codes (n = 3) or both (n = 15), depending on the study period. Most codes reported in literature were heterogeneous across complications/comorbidities. The medical coding expert and hematologist recommended modifications for several conditions. CONCLUSION: While many studies we identified did not report their codes and were excluded from this review, the studies with codes exhibited diverse coding definitions. By providing a standardized set of diagnosis codes that were reported by studies and reviewed by a coding expert and hematologist, our review can serve as a foundation for accurately identifying complications/comorbidities in future research, and may reduce heterogeneity, enhance transparency, and improve reproducibility. Future efforts focused on validating these code lists are needed.

Roadmap of Adversarial Machine Learning in Internet of Things-Enabled Security Systems.

Machine learning (ML) represents one of the main pillars of the current digital era, specifically in modern real-world applications. The Internet of Things (IoT) technology is foundational in developing advanced intelligent systems. The convergence of ML and IoT drives significant advancements across various domains, such as making IoT-based security systems smarter and more efficient. However, ML-based IoT systems are vulnerable to lurking attacks during the training and testing phases. An adversarial attack aims to corrupt the ML model's functionality by introducing perturbed inputs. Consequently, it can pose significant risks leading to devices' malfunction, services' interruption, and personal data misuse. This article examines the severity of adversarial attacks and accentuates the importance of designing secure and robust ML models in the IoT context. A comprehensive classification of adversarial machine learning (AML) is provided. Moreover, a systematic literature review of the latest research trends (from 2020 to 2024) of the intersection of AML and IoT-based security systems is presented. The results revealed the availability of various AML attack techniques, where the Fast Gradient Signed Method (FGSM) is the most employed. Several studies recommend the adversarial training technique to defend against such attacks. Finally, potential open issues and main research directions are highlighted for future consideration and enhancement.

Smart Spare Parts (SSP) in the Context of Industry 4.0: A Systematic Review.

The implementation of Industry 4.0 has integrated manufacturing, electronics, and engineering materials, leading to the creation of smart parts (SPs) that provide information on production system conditions. However, SP development faces challenges due to limitations in manufacturing processes and integrating electronic components. This systematic review synthesizes scientific articles on SP fabrication using additive manufacturing (AM), identifying the advantages and disadvantages of AM techniques in SP production and distinguishing between SPs and smart spare parts (SSPs). The methodology involves establishing a reference framework, formulating SP-related questions, and applying inclusion criteria and keywords, initially resulting in 1603 articles. After applying exclusion criteria, 70 articles remained. The results show that while SP development is advancing, widespread application of AM-manufactured SP is recent. SPs can anticipate production system failures, minimize design artifacts, and reduce manufacturing costs. Furthermore, the review highlights that SSPs, a subcategory of SPs, primarily differs by replacing conventional critical parts in the industry, offering enhanced functionality and reliability in industrial applications. The study concludes that continued research and development in this field is essential for further advancements and broader adoption of these technologies.