Screening Stage Research Articles

Assistive Technology to Support Dementia Management: Protocol for a Scoping Review of Reviews.

In Canada, more than 60% of persons living with dementia reside in their own homes, and over 25% rely heavily on their care partners (ie, family members or friends) for assistance with daily activities such as personal hygiene, eating, and walking. Assistive technology (AT) is a key dementia management strategy, helping to maintain health and social support in home and community settings. AT comprises assistive products and services required for safe and effective use. Persons living with dementia and their care partners often require multiple types of AT to maintain their needs, dignity, and autonomy. AT for dementia management is rapidly developing with abundant scientific literature, which can present a challenge to efficiently navigate and extract insightsfor policy and personal decision-making. This scoping review aims to synthesize review-level evidence from published scientific literature on AT to support dementia management for persons living with dementia and their care partners in their homes and communities. Research gaps in knowledge and areas for further investigation into the use and access of AT will be identified. This review will provide an overview of AT types and characteristics and chart the outcomes and conclusions in review-level evidence. This review will follow the Joanna Briggs Institute's framework for conducting scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. In total, 6 electronic databases will be searched. Articles will be screened according to the "Population-Concept-Context (PCC)" framework for eligible studies. Population includes persons living with dementia, their care partners, and health care professionals (eg, therapists or others who recommend AT). Concept includes AT and self-help devices of many types. Context includes homes and communities. A data charting template will guide data extraction, charting, and summarization. A descriptive numerical summary and an overview of the findings will be presented. Data, such as (1) article information (eg, author and year), (2) article characteristics (eg, review type), (3) AT types and characteristics, (4) setting and population characteristics, and (5) key review outcomes and conclusions, will be extracted. A total of 10,978 unique citations were identified across the 6 electronic databases. This review is in the full-text screening stage, which is expected to be completed by October 2024. This review will provide a comprehensive understanding and documentation of the published scientific literature on AT to support dementia management. Findings from this review are expected to provide evidence-based insights on the complexities of AT types, uses, availability, and access. The author group's diverse national and international perspectives may contribute to knowledge exchange and influence standards to improve the daily function, safety, and well-being of persons living with dementia. Open Science Framework DKSM9; https://osf.io/dksm9. PRR1-10.2196/57036.

Risk Management As A Determinant Of Indonesian Banking Financial Performance: A Systematic Literature Approach

This study aims to understand how risk management affects financial performance in the Indonesian banking sector. In a business environment full of uncertainty, especially in the banking sector, risk management is key to ensuring financial stability. Systematic Literature This review (SLR) analyzes the findings of articles published between 2016 and 2022, focusing on the main risks faced by banks: credit risk, market risk, liquidity risk, and operational risk. The selected articles were obtained from leading journal sources in the fields of economics and business. The literature selection process includes the stages of identification, screening, and thematic analysis to identify trends and correlations between risk management and financial performance indicators such as Return on Assets (ROA) and Return on Equity (ROE). The results of the study indicate that credit risk and operational risk have the most significant impact on financial performance, while market and liquidity risks show varying effects depending on the market situation and internal conditions of the bank. These findings underline the importance of a proactive approach to risk management, including the implementation of integrated risk mitigation policies and the use of effective internal controls. Thus, risk management not only serves as a safeguard against potential losses but also as a support for business sustainability. This study recommends further research to explore new risks such as cyber threats and regulatory changes, which are increasingly relevant in the context of the modern banking industry. These results are expected to provide insights for financial practitioners and banking leaders in improving the resilience and financial performance of their companies.

In silico prediction of the pharmacological potential of new 7-alkyl-8-hydrazine derivatives of 1,3-dimethylxanthine

The development of new drug-like molecules based on 7-R-8-hydrazine derivatives of 1,3-dimethylxanthine is promising in view of the known pharmacological effect of theophylline and functional hydrazine derivatives. In silico methods make it possible to rationalize the synthesis and reduce the number of chemical compounds at the stage of virtual screening by eliminating potentially ineffective molecules. The aim of the work was to carry out а virtual design and predictive evaluation of pharmacological activity of new 7-alkyl-8-hydrazine derivatives of 1,3-dimethylxanthine by in silico methods. Materials and methods. To perform in silico prediction of the pharmacological potential of several new 7-alkyl-8-hydrazine derivatives of 1,3-dimethylxanthine, we used the online services. As 12 model compounds, we chose 12 derivatives of 5-(2-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl)hydrazine)-5-phenylpentanoic acid with linear and branched alkyl substituents at the 7th position of the basic heterocycle: methyl-, ethyl-, n-propyl-, n-butyl, i-butyl, n-amyl, i-amyl, n-hexyl, n-heptyl, n-octyl, n-nonyl, n-decyl. The use of the freely available web tool SwissADME made it possible to calculate physicochemical parameters and to determine the drug-likeness properties of molecules. And other Internet platforms allowed to predict the spectrum of biological activity of the target compounds. Results. In silico analysis of the pharmacological potential of model compounds was performed. Three biological actions (peripheral vasodilator, kidney function stimulant, lipoprotein lipase inhibitor) with high Pa values are predicted for all derivatives of the series. The ADME parameters of the molecules were evaluated and their potential drug-like properties were determined. Conclusions. It was established that the extension of the alkyl substituent at the 7th position of the basic heterocycle should lead to a deterioration of the ADME parameters of the molecules, potentially reduce their oral bioavailability, but should not radically affect their biological activity profile. Compounds 1–3 and 5 are predicted to be orally bioavailable. They should be characterized by a wide spectrum of biological activity with the highest probability of vasodilator effect on peripheral vessels. In the future, it is advisable to carry out targeted synthesis of hit compounds and thorough in vitro, in vivo studies, and for compounds with violated physicochemical criteria – structural optimization of molecules in order to find a lead compound.

Toward a Typology of Business Groups: A Qualitative Content Analysis

By facilitating wider communication networks and improving the performance of their affiliated businesses in complex environments, businesses can increase their competitiveness. Understanding the characteristics and diversity of business groups is necessary for developing and implementing them. In this study, we examined the question of how business groups can be classified. What criteria can be used to separate them? We conducted a qualitative analysis of the content of 48 scientific journals published between 1999 and 2020 and selected 215 articles based on purposive sampling during two stages of screening. As a result of the content analysis, three main themes were identified: "origins of group control and ownership", "groups' institutional origins", and "intergroup relations". Also, at the first subtheme level, six categories were identified: group control level, group ownership type, diversity of group relations, dependence and cooperation level, relationship structure, and institutional contexts. There are 12 subcategories included in the second-level subthemes. "origin of corporate governance", "type of group ownership", "type of institutional contexts", "intra-group diversification", "extra-group diversification", "internal cooperation", "formalization ratio", "length of relations", "external cooperation", "geographical area", "depth of cooperation", "group maturity level". Lastly, axis factors related to the diversity of business groups were used to develop a set of typologies.

Skrining fitokimia tumbuhan potensi obat kanker kolorektal Begonia medicinalis Ardi & D.C. Thomas

Cancer is a condition in which cells or tissues undergo abnormal progressive growth. Colorectal cancer is cancer that occurs in the colon to rectum organs of humans. Alternative therapy for colorectal cancer treatment is the use of herbs such as Begonia medicinalis Ardi & D.C. Thomas. This study aimed to screen the bioactive compounds in the Begonia medicinalis Ardi & D.C. Thomas. extract and its potential as a colorectal cancer drug. This research consists of two stages, namely the extraction stage using the maceration method and the screening stage. The results showed that the extract of Begonia medicinalis Ardi & D.C. Thomas. positively contains flavonoids, alkaloids, and saponins. These bioactive compounds have potential activity as preventive and curative agents for colorectal cancer through several mechanisms, including suppressing oxidative stress, inhibiting CDK activity, suppressing intestinal inflammation, and increasing floranormal diversity and probiotic barrier activity in the intestine.

How can artificial intelligence impact the evaluation phase of a company takeover? Contribution of an in-depth case

Purpose AI has a leading influence and impact on organizations’ strategies. Yet few studies address how AI tools can impact M&A negotiation and the takeover evaluation stages of firms. Through an in-depth case study, our work questions how such tools can help with key stages of screening and due diligence periods. Design/methodology/approach We conduct several interviews with founders of the acquiring firm (Group Impact), and we had access to a large amount of information on the launch of the takeover process (including the data room of negotiation documents). Findings We detail the phases in which AI saved time (nongenerative AI) and, with a view to the future, we detail how a generative version of AI could help in the due diligence and negotiation phases. Also, we address the sticking points that prevented the takeover from being finalized. Originality/value First, few studies address the negotiation stage of takeovers as part of these are not finalized and, for the others, researchers are present in the field when the operation is signed. Second, studies that address takeovers that have failed are rare, yet understanding the blocking factors are essential to continue a long-term external growth strategy.

Auricular Therapy to Control Pain in Women With Breast Cancer: Protocol for Systematic Review and Meta-Analysis.

The increased incidence of breast cancer implies the appearance of frequent symptoms associated with disease and treatments, such as pain. For the management of this issue, auricular therapy has been used in a complementary manner, especially for its safety and analgesic action. This systematic review aims to summarize available evidence on the effects of auricular therapy on pain in women undergoing breast cancer treatment. This is a systematic review that includes randomized controlled trials that evaluated the effects of auricular therapy on pain in women with breast cancer, as compared with other interventions (sham or placebo auricular therapy, other nonpharmacological interventions, and routine pain treatments) during the treatment of the disease. Pain, whether induced or not by cancer treatments, is the main outcome to be evaluated. The search for the studies was performed in the following databases: MEDLINE through PubMed, CINAHL, CENTRAL, Embase, Web of Science, Scopus, VHL, TCIM Americas Network, CNKI, and Wanfang Data. The reviewers have independently evaluated the full texts, and in the near future, they will extract the data and assess the risk of bias in the included studies. The certainty of the evidence will be assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE), and a meta-analysis will be carried out to evaluate the intervention, considering the homogeneity of the results, using the Cochran Q test and quantified by the Higgins inconsistency index. The guidelines of the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) have been respected in the elaboration of this protocol. The records screening stage has been completed, and the synthesis and meta-analysis were conducted in February 2024. We hope to have finished the preparation of the paper for publication by September 2024. Review reporting will follow standard guidelines for reporting systematic reviews. The results will be published in peer-reviewed scientific journals. This review will compile the strength of evidence for the use of auricular therapy in the management of pain in women with breast cancer during the treatment of the disease, identifying gaps in the available evidence as well as assisting health professionals in indicating the intervention for clinical practice. PROSPERO CRD42022382433; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=382433. DERR1-10.2196/55792.

Promoting Language and Scientific Literacy Through Children's Literature: A Systematic Literature Review

ABSTRACT Children's literature is widely recognized for its potential to enhance student development. Despite existing research and publications on the topic, a thorough study on integrating children's literature into language and scientific literacy has not been widely conducted. This systematic literature review aimed to comprehensively explore current literature on innovative strategies and the effects of integrating children's literature to improve language and scientific literacy. Utilizing the Systematic Literature Review (SLR) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methods, this review analyzed 54 studies from the Scopus database spanning 2010 to 2024. The Publish or Perish and VOSviewer applications supported the identification, screening, eligibility, and inclusion stages. Scopus-indexed articles totaling 275 were initially identified and filtered into 54 relevant pieces. The findings highlight that integrating children's literature into science education effectively bridges language and scientific literacy, enhancing cognitive development and comprehension. The potential of this interdisciplinary teaching model suggests practical applications for educators seeking to enrich their instructional strategies by employing diverse literary forms such as informational texts, biographies, comics, dramas, and science fiction. Ultimately, this review emphasizes children’s literature's significant role in advancing language and scientific literacy in educational contexts. Keywords: children’s literature, language literacy, scientific literacy

Individual child factors affecting the diagnosis of attention deficit hyperactivity disorder (ADHD) in children and adolescents: a systematic review.

Attention deficit hyperactivity disorder (ADHD) is a prevalent condition characterised by patterns of inattention, hyperactivity, and impulsivity. This systematic literature review aims to identify the child clinical and sociodemographic factors related to the detection and diagnosis of ADHD in children and adolescents, given concerns about delays or failures in identifying ADHD as well as over-diagnosis, hindering appropriate and timely support for children and families. Through electronic and manual searches of peer-reviewed and grey literature, 5852 articles were identified and subjected to two stages of screening by independent reviewers. Due to the heterogeneity in study methods, a narrative approach was used to summarise study findings. Forty-one studies meeting eligibility criteria revealed sixteen child-related factors influencing the ADHD diagnostic process. These factors include ADHD subtype, ADHD symptom severity, comorbid mental disorders, behavior problems, internalizing symptoms, functional impairment, social and cognitive functioning, physical health, gender, age, relative age, race/ethnicity, socio-economic status, insurance coverage, residence urbanicity, and family structure. While the impact of many of these factors on ADHD diagnosis was inconsistent due to the substantial diversity in study designs and context, certain patterns emerged. Meeting the criteria for the inattentive subtype, lower functional impairment, female gender, Black or Latinx ethnicity, and being relatively young for their grade were consistently found to be associated with a delayed or absent ADHD diagnosis. Further research is needed to explore the intricate relationships between these child-level variables and their implications for ADHD recognition, referral, and evaluation, especially outside the USA.

Association between mammographic screening history and stage at diagnosis among women with screen-detected breast cancer.

145 Background: Although screening mammography is an effective means of detecting breast cancer at earlier stages, some women are still diagnosed with later stage disease despite screening mammography. We hypothesized that screening history prior to diagnosis may impact stage at diagnosis and breast cancer mortality among women with screen-detected breast cancer. Methods: Retrospective cohort study of women aged 70+ in the SEER-Medicare database, diagnosed with ER+/HER2- breast cancer from 2010-2017, and enrolled in fee-for service Medicare Parts A and B from 5-years prior to diagnosis through 1 year after. We used validated claims-based algorithms to identify cancers that were detected by screening mammogram. We quantified 5-year screening history by number of prior screens. Stage at diagnosis was dichotomized into very early (T1N0) vs. later stage (T2+ or N+) disease. Multivariable logistic regression was used to assess the association between screening history and stage at diagnosis and Cox proportional hazards used to examine breast cancer mortality. Models were adjusted for demographic and clinical covariates associated with later stage disease in bivariate analyses. Results: We included 13,029 women with screen-detected breast cancer; 3,813 (29.27%) women had later stage disease at diagnosis, and 10,095 (77.48%) had at least one prior negative screening mammogram within the past five years. During this time, 2,359 (18.11%) women had only one prior mammogram, 3,132 (24.03%) had two, and 4,604 (35.34%) had three or four. Having at least one prior mammogram was associated with 56% lower odds of being diagnosed with later stage disease (OR: 0.44, 95% CI=0.40-0.48). Sociodemographic factors associated with increased odds of later stage disease included living in an area with greater poverty (20-100% vs. 0-5% of residents, OR: 1.19, 1.00-1.40), non-Hispanic Black race (OR: 1.18, 1.00-1.38), and Medicare/Medicaid dual eligibility (OR: 1.20, 1.06-1.36). Factors associated with later stage disease included living in an area with a more people with a high-school education (30-40% vs. 0-30% of residents, OR: 0.87, 0.77-0.97). At total of 696 deaths from breast cancer were observed, including 273 deaths among 2,935 women with no prior screening (9.3%) and 423 deaths among 10,097 women who had undergone screening within the past five years (4.2%, P < 0.001). Receiving at least one negative screening prior to diagnosis was associated with decreased breast cancer-specific Mortality in adjusted analysis (HR: 0.48, 0.40-0.57). Conclusions: The use of prior routine screening mammography was associated with lower risk of being diagnosed with later stage disease and dying from breast cancer in elderly women with screen-detected breast cancer. Future research is warranted regarding the impact of routine vs. sporadic screening on potential morbidity and mortality in this age group.

The Association and diagnostic value between Maternal Serum Placental Markers and Placenta Previa

ObjectiveThis study aims to evaluate the correlation and diagnostic value of maternal serum placental markers: pregnancy-associated plasma protein-A (PAPP-A), free beta human chorionic gonadotropin (free β-hCG), and alpha fetoprotein (AFP) in relation to placenta previa. MethodsA retrospective case-control study was conducted to gather data on 137 pregnant women who were hospitalized for delivery at Hangzhou Obstetrics and Gynecology Hospital. These women participated in the late stage of early and mid-term maternal serum prenatal screening between January 2018 and December 2020. Of the 137 women, 45 were diagnosed with placenta previa, while 92 were selected at random as the control group, in a ratio of 1:2. Independent samples t-test or Mann-Whitney U test were utilized to compare the quantitative data of the two groups, and the Receiver operating characteristic curve (ROC) was used to evaluate the diagnostic value of maternal serum placental marker levels for placenta previa. ResultsThe levels of first trimester and second trimester free beta subunit of human chorionic gonadotropin (FT-Free β-hCG; ST-Free β-hCG) in the placenta previa group were higher than those in the normal group [1.38 (0.55-6.03) MoM vs.1.08 (0.32-4.00) MoM, 1.38 (0.39-4.10) MoM vs.1.01 (0.29-4.12) MoM], and the differences between the groups were statistically significant (Z = 2.830, Z = 2.846, both P < 0.05). The AFP level was higher than the normal group [1.13 (0.65-2.15) MoM vs. 0.94 (0.51-2.02) MoM], and the difference was statistically significant (Z = 2.551, P < 0.05). There was no significant difference in PAPP-A between the placenta previa group and the normal group (Z = 1.396, P > 0.05). The ROC curve analysis results showed that the AUCs of FT-Free β-hCG and ST-Free β-hCG for placenta previa were 0.649 (95% CI: 0.551-0.747, P=0.005), 0.634 (95% CI: 0.539-0.730, P=0.011), and 0.650 (95% CI: 0.554-0.746, P=0.004). Using PPV, NPV, FPR, FNR, +LR, and -LR as evaluation indicators for the 5 models, the results showed that FT-Free β-hCG was the best performer in terms of PPV, FPR, and +LR, with values of 0.725, 0.600, and 2.632, respectively. The three-indicator combined detection model (AFP + ST-Free β-hCG + FT-Free β-hCG) had the best performance in terms of NPV and -LR, with values of 0.770 and 0.298, respectively. ConclusionThe elevated maternal serum levels of Free β-hCG and AFP may be associated with placenta previa. The combined detection of maternal serum markers in the early and mid-trimesters has better diagnostic value for predicting placenta previa than individual detection.

Global mapping survey research on physiotherapeutic interventions for osteoarthritis: a scoping review protocol

IntroductionPhysiotherapists provide non-pharmacological conservative treatment for osteoarthritis (OA) using a wide spectrum of interventions. Previous surveys have identified global physiotherapy OA management practices. However, no review to date summarises the...

Federated influencer learning for secure and efficient collaborative learning in realistic medical database environment.

Enhancing deep learning performance requires extensive datasets. Centralized training raises concerns about data ownership and security. Additionally, large models are often unsuitable for hospitals due to their limited resource capacities. Federated learning (FL) has been introduced to address these issues. However, FL faces challenges such as vulnerability to attacks, non-IID data, reliance on a central server, high communication overhead, and suboptimal model aggregation. Furthermore, FL is not optimized for realistic hospital database environments, where data are dynamically accumulated. To overcome these limitations, we propose federated influencer learning (FIL) as a secure and efficient collaborative learning paradigm. Unlike the server-client model of FL, FIL features an equal-status structure among participants, with an administrator overseeing the overall process. FIL comprises four stages: local training, qualification, screening, and influencing. Local training is similar to vanilla FL, except for the optional use of a shared dataset. In the qualification stage, participants are classified as influencers or followers. During the screening stage, the integrity of the logits from the influencer is examined. If the integrity is confirmed, the influencer shares their knowledge with the others. FIL is more secure than FL because it eliminates the need for model-parameter transactions, central servers, and generative models. Additionally, FIL supports model-agnostic training. These features make FIL particularly promising for fields such as healthcare, where maintaining confidentiality is crucial. Our experiments demonstrated the effectiveness of FIL, which outperformed several FL methods on large medical (X-ray, MRI, and PET) and natural (CIFAR-10) image dataset in a dynamically accumulating database environment, with consistently higher precision, recall, Dice score, and lower standard deviation between participants. In particular, in the PET dataset, FIL achieved about a 40% improvement in Dice score and recall.

Optimized Machine Learning Classifiers for Symptom-Based Disease Screening

This work presents a disease detection classifier based on symptoms encoded by their severity. This model is presented as part of the solution to the saturation of the healthcare system, aiding in the initial screening stage. An open-source dataset is used, which undergoes pre-processing and serves as the data source to train and test various machine learning models, including SVM, RFs, KNN, and ANNs. A three-phase optimization process is developed to obtain the best classifier: first, the dataset is pre-processed; secondly, a grid search is performed with several hyperparameter variations to each classifier; and, finally, the best models obtained are subjected to additional filtering processes. The best-results model, selected based on the performance and the execution time, is a KNN with 2 neighbors, which achieves an accuracy and F1 score of over 98%. These results demonstrate the effectiveness and improvement of the evaluated models compared to previous studies, particularly in terms of accuracy. Although the ANN model has a longer execution time compared to KNN, it is retained in this work due to its potential to handle more complex datasets in a real clinical context.

Compartmentalization strategy for coastal flooding mitigation with application to a Northern Adriatic site

A method of compartmentalization has been developed to address the safety concerns of urban areas from coastal flooding, especially in situations where reinforcing the first line of defence (dunes, levees, etc.) is challenging due to, for instance, environmental limitations. Various compartmentalization options can be considered and evaluated in order to govern the flooding. Each option should be modelled with a suited numerical tool to better define the alternatives, determine the minimum height of the elements that bound the compartments and verify their effectiveness for the preliminary design, e.g. for the environmental screening stage. The methodology is demonstrated for a real case study, the flooding of Lido di Volano that occurred on November 22, 2022, using a simplified shallow water equations model designed for GPU computing to simulate large-scale flooding scenarios. Two compartmentalization schemes have been identified, both of which involve raising the existing road level. The maximum water levels in different zones of the study area are assessed as a function of crest height. These schemes have proven to be effective in protecting the urban settlement from flooding. Overall, the proposed method of compartmentalization, supported by a real case study analysis, offers a systematic approach to enhance the safety and the resilience of urban coastal areas. This type of solution capitalises on the experience of the local managers and technicians and may represent a shared solution among the coastal governance actors.

Show me the evidence to guide nutrition practice: Scoping review of macronutrient dietary treatments after metabolic and bariatric surgery.

Clinical practice recommendations for macronutrient intake in Metabolic and Bariatric Surgery (MBS) are insufficiently grounded in the research, possibly due to a paucity of research in key areas necessary to support macronutrient recommendations. An initial scoping review, prior to any systematic review, was determined to be vital. To identify topical areas in macronutrients and MBS with a sufficient evidence base to guide nutrition recommendations. PubMed, Cochrane, Ovid Medline, and Embase were initially searched in January 2019 (updated November 1, 2023) with terms encompassing current bariatric surgeries and macronutrients. Out of 757 records identified, 98 were included. A template was created. Five types of outcomes were identified for extraction: dietary intake, anthropometrics, adverse symptoms, health, and metabolic outcomes. All stages of screening and extraction were conducted independently by at least two authors and disagreements were resolved via team discussion. Macronutrient-related dietary treatments were classified as either innovative or standard of care. Descriptions of dietary arms were extracted in detail for a qualitatively generated typology of dietary or nutritional treatments. Heatmaps (treatments by outcomes) were produced to identify promising topics for further systematic analyses. We identified protein supplementation and "food-focused" (e.g., portion-controlled meals, particular foods in the diet, etc.) topical areas in MBS nutrition care with potentially sufficient evidence to create specific MBS Macronutrients guidelines and identified topical areas with little research. Clinical practice regarding macronutrient intake remains guided by consensus and indirect evidence. We detail ways that leadership at the profession level may remedy this.

Validated Administrative Data-Based ICD-10 Algorithms for Chronic Conditions

ObjectiveThis systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data. MethodsA comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70%. Studies with either sensitivity or PPV &lt;70% were included as secondary outcomes. ResultsOverall, the search identified 1686 studies of which 55 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. Of these, 30 studies demonstrated algorithms with high validity and 30 showed moderate validity. Studies with highly valid algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. Validated algorithms with PPV and sensitivity of ≥70% were identified for more than 40 chronic conditions that included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others. ConclusionWith ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

Virtual screening of drug materials for pharmaceutical tablet manufacturability with reference to sticking

The manufacturing of pharmaceutical solid dosage forms, such as tablets involves a large number of successive processing operations including crystallisation of the drug substance, granulation, drying, milling, mixing of the formulation, and compaction. Each step is fraught with manufacturing problems. Undesired adhesion of powders to the surface of the compaction tooling, known as sticking, is a frequent and highly disruptive problem that occurs at the very end of the process chain when the tablet is formed. As an alternative to the mechanistic approaches to address sticking, we introduce two different machine learning strategies to predict sticking directly from the chemical formula of the drug substance, represented by molecular descriptors. An empirical database for sticking behaviour was developed and used to train the machine learning (ML) algorithms to predict sticking properties from molecular descriptors. The ML model has successfully classified sticking/non-sticking behaviour of powders with 100% separation. Predictions were made for materials in the handbook of Pharmaceutical Excipients and a subset of molecules included in the ChemBL database, demonstrating the potential use of machine learning approaches to screen for sticking propensity early at drug discovery and development stages. This is the first-time molecular descriptors and machine learning were used to predict and screen for sticking behaviour. The method has potential to transform the development of medicines by providing manufacturability information at drug screening stage and is potentially applicable to other manufacturing problems controlled by the chemistry of the drug substance.

Research on the precise recognition stage of cerebral microhemorrhage based on deep learning algorithm

Cerebral microbleeds (CMB) is an important type of cerebral microbleeds. In recent years, many studies have proved that CMB can not only cause vascular dementia, but also increase the risk of stroke. Therefore, detection of CMB is of great clinical significance for balancing antithrombotic therapy and risk assessment in stroke patients, and detection of CMB is of great value for diagnosis and prognosis of cranial injury. This paper mainly proposes a two-stage CMB detection framework based on deep learning, which includes the screening stage of brain microhemorrhagic candidate points and the recognition stage of brain microhemorrhagic points based on deep learning. Firstly, in the first stage, we screened CMB candidate points by combining rapid radial transformation and threshold segmentation, and excluded a large number of background regions and obvious non-CMB regions. Then, in the second stage, the two-channel images spliced by sensitivity weighted imaging (SWI) and phase diagram (Pha) were used for false positive judgment by 3D convolutional neural network to distinguish the true CMB from the CMB analog.

Sources of Discrepancy between Retinal Nerve Fiber Layer and Bruch’s Membrane Opening-Minimum Rim Width Thickness in Eyes with Glaucoma

To compare the discrepancies between circumpapillary retinal nerve fiber layer (RNFL) and Bruch's membrane opening-minimum rim width (BMO-MRW) thickness in glaucoma eyes. A cross-sectional observational study. One hundred eighty-six eyes (118 patients) with glaucoma. OCT optic nerve head volume scans of patients enrolled in the Advanced Glaucoma Progression Study at the final available visit were exported. The RNFL and BMO-MRW measurements were averaged into corresponding 7.5° sectors, and the nasal sector data were excluded from analyses. A 2-stage screening process was used to identify true mismatches between the RNFL and BMO-MRW measurements, in which either the RNFL or BMO-MRW value was in the less than first percentile range while its counterpart was in the greater than first percentile range on the temporal-superior-nasal-inferior-temporal curve. The prevalence of these mismatches was mapped, and corresponding images were reviewed to determine the underlying cause of these discrepancies. Proportion of mismatches between RNFL and BMO-MRW, location of mismatches between RNFL and BMO-MRW, anatomical causes of mismatches between RNFL and BMO-MRW. Mismatch analysis revealed true mismatches between RNFL and BMO-MRW in 7.7% of sectors. High BMO-MRW with low corresponding RNFL mismatches were most frequently located at the 45° and 322.5° sectors, whereas high RNFL with corresponding low BMO-MRW mismatches peaked at the 75° sector. Large blood vessels accounted for 90.9% of high RNFL with low BMO-MRW mismatches. Small to large blood vessels accounted for 62.9% of high BMO-MRW with low RNFL mismatches; the remaining mismatches could be attributed to retinoschisis or inclusion of outer retinal layers in BMO-MRW measurements. Although overall agreement between RNFL and BMO-MRW measurements is good in areas with advanced damage, blood vessels and other anatomical factors can cause discrepancies between the 2 types of structural measurements and need to be considered when evaluating the utility of such measurements for detection of change. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.