Information Quality Assessment Research Articles

#PapSmear on TikTok: User Sentiments and Health Information [ID 2683630

INTRODUCTION: TikTok has emerged as a leading social media platform, with many users using the app for educational purposes, including for discussions about obstetrics and gynecology. We assessed tone, content, and quality of health information of TikTok videos tagged with #PapSmear. METHODS: One hundred videos tagged with #PapSmear on TikTok were collected using the data-scraping program, Apify (Prague, Czech Republic). Videos were extracted with their number of views, likes, comments, and shares, and analyzed for tone, themes, creator demographics and health information quality. Two modified standardized scales were used: DISCERN, for health information quality and Patient Education Materials Assessment Tool (PEMAT), for understandability and actionability. RESULTS: We reviewed 93 of 100 videos tagged with #PapSmear. Videos received 237 million views, 19 million likes, and 241 thousand comments in total. Videos were coded as positive (26.9%), negative (37.6%), and neutral (35.5%). Medical professionals created most of the positive videos (68.0%), whereas most negative video creators were not medical professionals (91.4%). Nearly half of positive videos were educational (48.0%), and most negative videos recounted personal patient experiences (60.0%). Videos scored high on understandability (average 73.4%, SD 16.3%) but low on actionability (average 31.9%, SD 34.1%) and quality of health information (2.12, SD 0.4). CONCLUSION: There is a discrepancy in tone between patients and medical professionals in videos tagged with #PapSmear. Videos with educational material were easy to understand, but provided low-quality health information and did not effectively highlight opportunities for patient action. Negative influence from TikTok should be considered in patient–provider communication about Pap smears.

Risk Management in Agile Al/Ml Projects: Identifying and Mitigating Data and Model Risks

Purpose: This study addresses the crucial challenge of managing risks associated with data and models in Agile Artificial Intelligence (AI) and Machine Learning (ML) projects. It aims to develop a systematic framework for effective risk control utilizing agile methodologies. Methodology: The research is grounded in an interpretivist approach and utilizes a deductive method. It constructs a comprehensive framework for identifying and mitigating risks, integrating risk management seamlessly into Agile processes for AI and ML development. Findings: The study introduces four technological themes critical for risk mitigation: dynamic distribution of resources, model robustness, risk integration, and quality assessment of information. These themes provide actionable strategies for reducing risks throughout the Agile AI/ML development lifecycle, ensuring that risk assessment and mitigation are integral to project planning and execution. Unique contribution to theory, practice, and policy: The study contributes to both theory and practice by offering a detailed, actionable framework for risk management in Agile AI/ML projects. It advocates for the adoption of adaptive technologies and tools, continuous stakeholder engagement, and adherence to ethical standards. Recommendations include validation of the framework through empirical research and ongoing longitudinal evaluations to adapt and refine risk management practices. This approach aims to enhance the reliability and efficiency of project outputs in dynamic environments, providing a significant foundation for policy development in technology project management.

The structure assessment web server: for proteins, complexes and more.

The 'structure assessment' web server is a one-stop shop for interactive evaluation and benchmarking of structural models of macromolecular complexes including proteins and nucleic acids. A user-friendly web dashboard links sequence with structure information and results from a variety of state-of-the-art tools, which facilitates the visual exploration and evaluation of structure models. The dashboard integrates stereochemistry information, secondary structure information, global and local model quality assessment of the tertiary structure of comparative protein models, as well as prediction of membrane location. In addition, a benchmarking mode is available where a model can be compared to a reference structure, providing easy access to scores that have been used in recent CASP experiments and CAMEO. The structure assessment web server is available at https://swissmodel.expasy.org/assess.

Advanced Linguistic Complex T-Spherical Fuzzy Dombi-Weighted Power-Partitioned Heronian Mean Operator and Its Application for Emergency Information Quality Assessment

Against the background of a major change in the world unseen in a century, emergencies with high complexity and uncertainty have had serious impacts on economic security and sustainable social development, making emergency management an important issue that needs to be urgently resolved, and the quality assessment of emergency information is a key link in emergency management. To effectively deal with the uncertainty of emergency information quality assessment, a new fuzzy multi-attribute assessment method is proposed in this paper. First, we propose the linguistic complex T-spherical fuzzy set (LCT-SFS), which can deal with two-dimensional problems and cope with situations in which assessment experts cannot give quantitative assessments. Then, the advanced linguistic complex T-spherical fuzzy Dombi-weighted power-partitioned Heronian mean (ALCT-SFDWPPHM) operator, which incorporates the flexibility of Dombi operations, is proposed. The partitioned Heronian mean (PHM) operator can consider attribute partitioning and attribute correlation, the power average (PA) operator can eliminate the effect of evaluation singularities, and the advanced operator can circumvent the problem of consistent or indistinguishable aggregation results, which provides a strong comprehensive advantage in the evaluating information aggregation. Finally, a fuzzy multi-attribute assessment model is constructed by combining the proposed operator with the WASPAS method and applied to the problem of assessing the quality and sensitivity of emergency information; qualitative and quantitative comparison analyses are carried out. The results show the method proposed in this paper has strong feasibility and validity and can represent uncertainty assessment more flexibly while providing reasonable and reliable results. The method can provide new ideas and methods for the quality assessment of emergency information, and promoting sustainable, efficient, and high-quality development of emergency management.

Exploring the Learner Information System (LIS): A Usability Assessment on Enhanced Facility for Educators

A Learner Information System (LIS) is a web- based tool that serves as a database for all students enrolled in basic education. The department implemented several facility enhancements to address identified problems with enrolling students, updating their profiles and statuses, and generating reports. However, to determine whether the system's facility augmentation is effective, it is crucial to look at the system's usability from the viewpoint of the end- user. This study aims to evaluate users’ usability assessment of system quality, information quality, and interface quality of the system. A survey-type study that utilized a mixed method and adopted the Lewis Computer System Usability Questionnaire (CSUQ) with 19 questions and used a 7-point Likert scale. The study used convenience sampling of 30 out of 54 junior and senior high school teacher-advisers. The result of the study indicates that the responses have a positive perception of the three main factors of system usability assessment. The result also shows that only the information quality indicator significantly affects the length of service. Overall, the respondents were satisfied with their user’s experience on the LIS.

Quality and Readability Assessment of Web-based Arabic Health Information on Early Childhood Caries.

Patients are increasingly using the internet for searching health-related information. However, the quality and readability of the information available on the internet need to be assessed. To date, no study has assessed the quality and readability of web-based Arabic health information on early childhood caries. To evaluate the quality and readability of patient-oriented online Arabic health information regarding early childhood caries. For this infodemiological study, the Google and Yahoo search engines were searched using specific Arabic terms for early childhood caries, and the top 100 searches from both search engines were considered. Eligible websites were categorized in terms of affiliation as commercial, health portal, dental practice, professional, and journalism. The quality of the websites was assessed using the QUality Evaluation Scoring Tool (QUEST), and readability using the Gunning Fog index (GFI). A total of 140 websites were included after applying the exclusion criteria, of which 50.7% websites were of journalism. The majority of the websites (70%) had an overall low-quality level, with a QUEST score <10. The quality of websites retrieved from Google searches was of significantly higher quality than those from Yahoo (P < 0.0001). More than half (51.4%) of the websites had good readability, with a GFI score ≤8. Journalism websites had a significantly higher proportion of websites with poor readability level (62%) compared with other affiliations (P = 0.0072). The web-based Arabic information regarding early childhood caries is currently of low quality and moderate readability level, thereby indicating a need for improving such patient-facing content.

Quality assessment of available Internet information on early orthodontic treatment

BackgroundThis study aimed to evaluate the content, reliability, quality and readability of information on Internet websites about early orthodontic treatment.MethodsThe “early orthodontic treatment” search term was individually entered into four web search engines. The content quality and reliability were reviewed with DISCERN, Journal of American Medical Association (JAMA), and Health on the Net code (HONcode) tools using the contents of websites meeting predetermined criteria. The readability of websites was evaluated with Flesch Reading Facilitate Score (FRES) and Flesch–Kincaid Grade Level (FKGL).ResultsEighty-six websites were suitable for inclusion and scoring of the 200 websites. 80.2% of websites belonged to orthodontists, 15.1% to multidisciplinary dental clinics and 4.7% to professional organizations. The mean DISCERN score of all websites (parts 1 and 2) was 27.98/75, ranging between 19 and 67. Professional organization websites had the highest scores for DISCERN criteria. Moreover, 45.3% of websites were compatible with JAMA’s disclosure criterion, 7% with the currency criterion, 5.8% with the authorship criterion and 5.8% with the attribution criterion. Only three websites met all JAMA criteria, and these websites belonged to professional organizations. None of the websites had the HONcode logo. Mean FRES and FKGL were 47.6 and 11.6, respectively.ConclusionsThe quality of web-based information about early orthodontic treatment is poor, and readability is insufficient. More accurate and higher quality Internet sources are required on the web.

Health Information Quality of Online Newspaper Articles in Korea.

The Web is an important source of health information, but the quality of such online information is highly variable. This study evaluates the quality of health articles published on Naver News, Korea's most popular portal, using the Health Information Quality Assessment Tool (HIQUAL). We collected 712 health-related articles published on Naver News from May 1 to 7, 2023. After applying exclusion criteria, we selected 116 articles for analysis. Two clinicians independently assessed the quality of these articles using the HIQUAL, which scores articles based on five domains: "reliability," "usefulness," "understandability," "sufficiency," and "transparency." Overall article quality was generally considered recommendable (mean±standard deviation: 7.52±2.00). "Usefulness," one item of "reliability," and "understandability" were the three items with the highest levels of satisfaction. "Sufficiency" criteria for costs, risks, and benefits received low scores. Quality scores for articles focused on health risk factors and intervention showed a statistically significant difference. While the overall quality of health information in Korean online newspaper articles is acceptable, room for improvement remains in some areas, particularly with regard to the fair presentation of costs, risks, and benefits. The study highlights the need for ongoing quality improvement and evaluation initiatives for online health information.

Credibility of EWOM and Consumer Satisfaction on Food/Health Supplement Products during the COVID-19 Pandemic

During the pandemic, many information about the function of various food and health supplement products for prevention/recovery from Covid-19 infection circulated through EWOM (electronic word of mouth), which was believed by consumers, even though not all of them were proven to be true. This study aims to examine the role of perceived EWOM credibility on consumer satisfaction with food/health supplement products during the COVID-19 pandemic. The theoretical framework guiding this research is Source Credibility Theory, which provides a lens to examine how the credibility of EWOM sources affects consumer satisfaction. The participants were 103 people aged 19-25 years who had purchased and consumed food/health supplement products during the COVID-19 pandemic and had read EWOM about information/reviews of the products they consumed. Participants filled out a questionnaire that measured their perceived EWOM credibility and consumer satisfaction. The data were analyzed using multiple linear regression. The results showed that perceived EWOM credibility positively influenced consumer satisfaction. Aspects of perceived EWOM credibility, included argument quality and homophily had a significant influence on consumer satisfaction. The quality of arguments positively contributes to enhancing customer satisfaction, whereas homophily, on the other hand, has a negative impact. Consequently, a heightened perception of EWOM credibility, particularly concerning the quality of argument presented directly correlated with increased participant satisfaction with the food/health supplement products they had consumed. The findings of this study hold practical implications for the promotion of food and health supplements, emphasizing the significance of EWOM credibility. Additionally, the results underscore the importance of fostering information literacy among consumers in this domain. For instance, strategies could include the dissemination of infographics illustrating methods to assess information quality and discern genuine information from hoaxes. On the other hand, relying solely on information based on shared backgrounds does not fully support the attainment of satisfaction in consumption.

Quality assessment of online patient information on upper gastrointestinal endoscopy using the modified Ensuring Quality Information for Patients tool.

Websites and online resources are increasingly becoming patients' main source of healthcare information. It is paramount that high quality information is available online to enhance patient education and improve clinical outcomes. Upper gastrointestinal (UGI) endoscopy is the gold standard investigation for UGI symptoms and yet little is known regarding the quality of patient orientated websites. The aim of this study was to assess the quality of online patient information on UGI endoscopy using the modified Ensuring Quality Information for Patients (EQIP) tool. Ten search terms were employed to conduct a systematic review. for each term, the top 100 websites identified via a Google search were assessed using the modified EQIP tool. High scoring websites underwent further analysis. Websites intended for professional use by clinicians as well as those containing video or marketing content were excluded. A total of 378 websites were eligible for analysis. The median modified EQIP score for UGI endoscopy was 18/36 (interquartile range: 14-21). The median EQIP scores for the content, identification and structure domains were 8/18, 1/6 and 9/12 respectively. Higher modified EQIP scores were obtained for websites produced by government departments and National Health Service hospitals (p=0.007). Complication rates were documented in only a fifth (20.4%) of websites. High scoring websites were significantly more likely to provide balanced information on risks and benefits (94.6% vs 34.4%, p<0.001). There is an immediate need to improve the quality of online patient information regarding UGI endoscopy. The currently available resources provide minimal information on the risks associated with the procedure, potentially hindering patients' ability to make informed healthcare decisions.

Assessment of Financial Information Quality: Evidence from Tunisian Context

The present paper aims at assessing the financial information quality within Tunisian firms. We analyzed a sample annual data of 78 financial and non-financial Tunisian listed companies. We use the level of discretionary accruals and if the firm restate its financial statement or not as proxies of financial information quality. Our main results show that the financial information quality is globally low. We note a high level of discretionary accruals within financial firms compared to non-financial pears. We also find that financial firms are less likely to restate their financial statements compared to those of non-financial firms.

CONTENT EVALUATION OF DIAGNOSTIC AND TREATMENT INFORMATION QUALITIES OF YOUTUBE VIDEOS ON CARPAL TUNNEL SYNDROME

Introduction: One of the leading video sharing platforms is YouTube (YT). Due to their increased use, these can possibly create misconceptions about the condition, especially the associated treatment and signs and symptoms of carpal tunnel syndrome. Thus, this evaluates the information quality of YT videos about carpal tunnel syndrome (CTS). Methods: This is a descriptive-evaluated study focused on assessing the information qualities of CTS videos on YT. Using Macleod et al. information quality index (2015), modified Diagnostic Information Quality Assessment Checklist (DIQAC) and Treatment Information Quality Assessment Checklist (TIQAC) were utilized. DIQAC measures the elements explanation, history, physical examination and ancillary procedures; while TIQAC, presurgical, surgical procedure, rehabilitation and complication elements. YT videos from 2020 onwards were searched using keywords "carpal tunnel syndrome", "diagnosis" and "treatment", and screened for duplicates, non-related to topic and without audio. Out of 31 videos retrieved, 11 YT videos on CTS were evaluated by physical therapists to determine the reliability of YT videos on CTS. Results: Results showed that YT-CTS videos are highly reliable in the elements explanation (45%) and history (36.36%), moderate to reliable in ancillary procedure (54.54%) and moderately reliable in physical examination (36%), in terms of DIQAC scoring. Whereas in TIQAC scoring, YT-CTS videos obtained a highly reliable presurgical scoring (45.45%). Surprisingly, it is poorly reliable in complication scoring (45.45%), very poorly to poor reliable in rehabilitation scoring (72.72%), and very poorly reliable in surgical scoring (45.45%). Overall, diagnosis information quality is high (65%), but low treatment information quality (32%). Discussion: This demonstrates that YT videos are technological tool that a physical therapist or a clinicians can utilize to educate and diagnose. Treatment information can hardly be explained in videos, which can vary form case to case, and is best explained through medical advice of a doctor to his patient with CTS.

Evaluation of three prediction formulas of 24-hour urinary sodium excretion in Chinese residents: a systematic review and meta-analysis.

To determine the appropriateness of three widely used formulas estimating 24-h urinary Na (24hUNa) from spot urine samples in the Chinese population. Systematic review and meta-analysis. Literature review was conducted to identify studies for estimating 24hUNa using the Kawasaki, Tanaka and INTERSALT formulas simultaneously in PubMed, Embase and the Cochrane library databases. The mean difference (MD) and correlation coefficients (r) between measures and estimates from different formulas were assessed. Information extraction and quality assessment were performed in thirteen studies involving 8369 subjects. Two studies which affected the overall robustness were excluded in the 'leave-one-out' sensitivity analyses. Within the final meta-analysis included eleven studies and 7197 participants, 36·07 mmol/d (95 %CI 16·89, 55·25) of MD was observed in the Kawasaki formula, and -19·62 mmol/d (95 %CI -37·37, -1·87) in the Tanaka formula and -35·78 mmol/d (95 %CI -50·76, -20·80) in the INTERSALT formula; a pooled r-Fisher's Z of 0·39 (95 %CI 0·32, 0·45) in the Kawasaki formula, 0·43 (95 %CI 0·37, 0·49) in the Tanaka formula and 0·36 (95 %CI 0·31, 0·42) in the INTERSALT formula. Subgroup analyses were conducted to explore the possible factors affecting the accuracy of the formula estimation from three mainly aspects: population types, Na intake levels and urine specimen types. The meta-analysis suggested that the Tanaka formula performed a more accurate estimate in Chinese population. Time of collecting spot urine specimens and Na intake level of the sample population might be the main factors affecting the accuracy of the formula estimation.

Quality Assessment of Degenerative Cervical Myelopathy Information on the Internet.

Patient education is a key element of spinal surgery informed consent. Patients frequently access health information online, yet this information is unregulated and of variable quality. We aimed to assess the quality of information available on degenerative cervical myelopathy (DCM) websites with a focus on identifying high-quality information websites. We performed a Google search using keywords pertaining to DCM. The top 50 websites returned were classified based on their publication source, intended audience, and country of origin. The quality of these websites was assessed using both the DISCERN instrument and Journal of the American Medical Association (JAMA) benchmark criteria. We also utilized a novel Myelopathy Information Scoring Tool (MIST) to assess the comprehensiveness, accuracy, and detail of online DCM information. The mean DISCERN score was 39.9 out of 80. Only one-quarter of these websites were rated "good" or "excellent" using DISCERN, and the remaining were rated "very poor," "poor," and "fair." The mean JAMA benchmark score was 1.6 out of 4, with 23 out of 50 websites scoring 0. Evaluation using MIST found a mean score of 25.6 out of 50. Using 30 points as a satisfactory MIST cutoff, 72% of DCM websites were deemed critically deficient and unsatisfactory for comprehensive patient education. Both DISCERN and MIST indicated poorest information pertaining to surgical risks and complications as well as treatment outcomes. Websites such as Orthoinfo.aaos.org and Myelopathy.org provided reliable, trustworthy, and comprehensive patient education. Information available on almost three-quarters of DCM websites was of poor quality, with information regarding complications and treatment outcomes most deficient. Clinicians should be aware of quality sites where patients may be directed to augment patient education and surgical counseling.

Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants

AbstractEvaluating information quality online is increasingly important for healthy decision‐making. People assess information quality using visual interfaces (e.g., computers, smartphones) with visual cues like aesthetics. Yet, voice interfaces lack critical visual cues for evaluating information because there is often no visual display. Without ways to assess voice‐based information quality, people may overly trust or misinterpret information which can be challenging in high‐risk or sensitive contexts. This paper investigates voice information uncertainty in one high‐risk context—health information seeking. We recruited 30 adults (ages 18–84) in the United States to participate in scenario‐based interviews about health topics. Our findings provide evidence of information uncertainty expectations with voice assistants, voice search preferences, and the audio cues they use to assess information quality. We contribute a nuanced discussion of how to inform more critical information ecosystems with voice technologies and propose ways to design audio cues to help people more quickly assess content quality.

Can ChatGPT Aid Clinicians in Educating Patients on the Surgical Management of Glaucoma?

ChatGPT can help health care providers automate the quality assessment of online health information, but it does not produce easier-to-understand responses compared with existing online health information. To compare the readability of ChatGPT-generated health information about glaucoma surgery to existing material online and to evaluate ChatGPT's ability to analyze the quality of information found online about glaucoma surgery. ChatGPT was asked to create patient handouts on glaucoma surgery using 7 independent prompts, aiming to generate sixth grade level reading material. Existing patient-targeted online health information about glaucoma surgery was selected from the top 50 search results of 3 search engines, excluding advertisements, blog posts, information intended for health professionals, irrelevant content, and duplicate links. Four validated tools were used to assess readability, and the readability of the ChatGPT-generated material was compared with the readability of existing online information. The DISCERN instrument was used for the quality assessment of online materials. The DISCERN instrument was also programmed to use ChatGPT to evaluate its ability to analyze quality. R software and descriptive statistics were used for data analysis. Thirty-five webpages were included. There was no difference between the reading level of online webpages (12th grade) and the reading level of ChatGPT-generated responses (11th grade), despite the ChatGPT prompts asking for simple language and a sixth grade reading level. The quality of health content was "fair," with only 5 resources receiving an "excellent" score. ChatGPT scored the quality of health resources with high precision ( r =0.725). Patient-targeted information on glaucoma surgery is beyond the reading level of the average patient, therefore at risk of not being understood, and is of subpar quality, per DISCERN tool scoring. ChatGPT did not generate documents at a lower reading level as prompted, but this tool can aid in automating the time-consuming and subjective process of quality assessment.

Readability and Quality Assessment of Web-Based Information Concerning Post-Endodontic Treatment Selection

Objectives: This study aimed to unbiasedly identify the quality and readability of the written information about post-endodontic coronal restorations on Turkish websites using accepted formulas and scales by the literature.&#x0D; Methods: The study was carried out by setting national pages and national locations in the Google search engine. The terms "root canal treatment and veneer" and "root canal treatment and filling" were used as keywords. The webpages were assessed independently by two readability formulas (Flesh-Kincaid and Ateşman systems) and DISCERN quality kit. The independent statistical and correlation analysis were performed using Kolmogorov-Smirnov, Shapiro-Wilk, Spearman's rho, and Dunn's tests. The significance level was taken as p&lt;0.05.&#x0D; Results: The initial search identified 60 websites, of which eight were excluded due to non-compliance with the study criteria (n=52). According to the DISCERN score, the web pages were categorized as fair with the highest rate of 57.69%. A statistically significant positive correlation was found between Ateşman Readability Index and the Flesh-Kincaid Reading Ease score (r=0.998; p&lt;0.001). There was no statistically significant correlation between Ateşman Readability Index and DISCERN score (p=0.259). Ateşman reading ease scores of the web pages are evaluated, 80.76% of these are classified as moderately difficult.&#x0D; Conclusions: The readability distribution of the written information about post-endodontic coronal restorations on websites was acceptable to the majority. However, being readable does not indicate that it provides sufficient target technical information. In this context, it can be suggested to use readability and quality scales while preparing websites for dental patient education concerning post-endodontic coronal restorations.

Crowds Can Effectively Identify Misinformation at Scale

Identifying successful approaches for reducing the belief and spread of online misinformation is of great importance. Social media companies currently rely largely on professional fact-checking as their primary mechanism for identifying falsehoods. However, professional fact-checking has notable limitations regarding coverage and speed. In this article, we summarize research suggesting that the “wisdom of crowds” can be harnessed successfully to help identify misinformation at scale. Despite potential concerns about the abilities of laypeople to assess information quality, recent evidence demonstrates that aggregating judgments of groups of laypeople, or crowds, can effectively identify low-quality news sources and inaccurate news posts: Crowd ratings are strongly correlated with fact-checker ratings across a variety of studies using different designs, stimulus sets, and subject pools. We connect these experimental findings with recent attempts to deploy crowdsourced fact-checking in the field, and we close with recommendations and future directions for translating crowdsourced ratings into effective interventions.

Tire-Road Peak Adhesion Coefficient Estimation Based on Multisource Information Assessment

The tire-road peak adhesion coefficient (TRPAC) is defined as the ratio of the peak adhesion to the vertical load of the tire, which can characterize the ability of a tire to adhere to the road. Reliable TRPAC estimation can not only benefit the vehicle active safety system, but also serve the intelligent transportation system to improve the safety of traffic participants. Considering the problems of low estimation accuracy and poor real-time performance caused by low-quality sensor information in existing TRPAC estimation methods, a TRPAC fusion estimation framework based on the assessment of multisource information quality is proposed in this paper. Based on the observability theory of nonlinear systems, a quantitative indicator of dynamic information quality denoted as the excitation level is established. The region of effective excitation is defined as the criterion for starting and stopping the proposed dynamics-based fusion estimator for the longitudinal-lateral coupling condition. Considering occupant comfort and vehicle stability, an active enhancement method based on hierarchical model predictive control is designed to actively improve the excitation level. Based on the receding horizon optimization theory, a dynamics-image-based fusion estimator is proposed to make full use of visual and dynamic information. An adaptive fusion estimation strategy is then proposed to apply the proper estimation working mode according to the multisource information quality. The results of the simulation and vehicle test show that the proposed framework can still perform competitively when the quality of multisource information is poor and achieve reliable TRPAC estimation.

Explainable human‐in‐the‐loop healthcare image information quality assessment and selection

AbstractSmart healthcare applications cannot be separated from healthcare data analysis and the interactive interpretability between data and model. A human‐in‐the‐loop active learning approach is introduced to reduce the cost of healthcare data labelling by evaluating the information quality of unlabelled medical data and then screening the high informative samples. Specifically, focused on the extracted feature tensor of medical images, a new evaluation metric was proposed, called local feature information distance. Then, the whole feature information distance between two images can be obtained by seeking optimal matching of local feature information correlation based on the feature spatial traversal. Further, the feature information distance entropy (FIDE) method was proposed from the perspective of feature spatial distribution, which outperformed other related works. Many comparison and ablation experiments were carried out; the results showed that the proposed method can well distinguish the information quality of the unlabelled samples even facing different datasets. The stability, robustness, and generalisation of the proposed method were verified. Thus, this study provides some inspirations for healthcare data analysis and efficient management, such as eliminating redundancy and selective annotation.