Decision Confidence Research Articles

Evaluation of clinical and imaging features for differentiating rhabdomyosarcoma from neuroblastoma in pediatric soft tissue.

In this study, we developed a nomogram predictive model based on clinical, CT, and MRI parameters to differentiate soft tissue rhabdomyosarcoma (RMS) from neuroblastoma (NB) in children preoperatively. A total of 103 children with RMS (n=37) and NB (n=66) were enrolled in the study from December 2012 to July 2023. The clinical and imaging data (assessed by two experienced radiologists) were analyzed using univariate analysis, and significant factors were further analyzed by multivariable logistic regression using the forward LR method to develop the clinical model, radiological model, and integrated nomogram model, respectively. The diagnostic performances, goodness of fit, and clinical utility of the integrated nomogram model were assessed using the area under the curve (AUC) of the receiver operator characteristics curve (ROC) with a 95% confidence interval (95% CI), calibration curve, and decision curve analysis (DCA) curves, respectively. Diagnostic efficacy between the model and radiologists' interpretations was examined. The median age at diagnosis in the RMS group was significantly older than the NB group (36.0 months vs. 14.5 months; P=0.003); the fever rates in RMS patients were significantly lower than in patients with NB (0.0% vs.16.7%; P=0.022), and the incidence of palpable mass was higher in patients with RMS compared with the NB patients (89.2% vs. 34.8%; P<0.001). Compare NB on image features: RMS occurred more frequently in the head and neck and displayed homogeneous density on non-enhanced CT than NB (48.6% vs. 9.1%; 35.3% vs. 13.8%, respectively; all P<0.05), and the occurrence of characteristics such as calcification, encasing vessels, and intraspinal tumor extension was significantly less frequent in RMS children compared to children with NB (18.9% vs. 84.8%; 13.5% vs. 34.8%; 2.7% vs. 50.0%, respectively; all P <0.05). Two, three, and four features were identified as independent parameters by multivariate logistic regression analysis to develop the clinical, radiological, and integrated nomogram models, respectively. The AUC value (0.962), calibration curve, and DCA showed that the integrated nomogram model may provide better diagnostic performance, good agreement, and greater clinical net benefits than the clinical model, radiological model, and radiologists' subjective diagnosis. The clinical and imaging features-based nomogram has potential for helping radiologists distinguish between pediatric soft tissue RMS and NB patients preoperatively, and reduce unnecessary interventions.

Refining expected market return estimation: fusing multiple valuation models as an approach to reducing uncertainty

This paper presents a methodology aimed at reducing the uncertainty associated with estimating the expected market return within a bounded rationality framework. The proposed approach involves calculating the implicit rate of return using various valuation models and subsequently merging them using the Kalman Filter technique to minimize estimation errors. The contribution of this study lies in the application of the Kalman Filter, which enables the expected market return to be refined and provides a more accurate estimate by mitigating uncertainty. The ability to determine an accurately expected market return assumes critical significance in investment decision-making. Therefore, investors can utilize this methodology as a tool to enhance the precision of their investment choices. By reducing uncertainty in estimating the expected market return, this approach empowers investors to make more informed and confident decisions.

Utility of Prostate Health Index Density for Biopsy Strategy in Biopsy-Naïve Patients With PI-RADS v2.1 Category 3 Lesions.

Category 3 lesions in PI-RADSv2.1 pose diagnostic challenges, complicating biopsy decisions. Recent biomarkers like prostate health index (PHI) have shown higher specificity in detecting clinically significant prostate cancer (csPCa) than prostate-specific antigen (PSA). Yet their integration with MRI remains understudied. To evaluate the utility of PSA and PHI with its derivatives for detecting csPCa in biopsy-naïve patients with category 3 lesion on initial prostate MRI scan. Retrospective. One hundred ninety-three biopsy-naïve patients who underwent MRI, PSA, and PHI testing, followed by both targeted and systematic biopsies. Turbo spin-echo T2-weighted imaging, diffusion-weighted single-shot echo-planar imaging, and dynamic contrast-enhanced T1-weighted fast field echo sequence imaging in 3 T. PHI density (PHID) and PSA density (PSAD) derived by dividing serum PHI and PSA with prostate volume (MRI based methodology suggested by PI-RADSv2.1). Risk-stratified models to evaluate the utility of markers in triaging patients for biopsy, including low-, intermediate-, and high-risk groups. Independent t-test, Mann-Whitney U test, Mantel-Haenszel test, generalized estimating equation, and receiver operating characteristic (ROC) curve analysis were used. Statistical significance defined as P < 0.05. CsPCa was found in 16.6% (32/193) of patients. PHID had the highest area under the ROC curve (AUROC) of 0.793, followed by PHI of 0.752, PSAD of 0.750, and PSA of 0.654. PHID with two cut-off points (0.88/mL and 1.82/mL) showed the highest potential biopsy avoidance of 47.7% (92/193) with 5% missing csPCa, and the lowest intermediate-risk group (borderline decision group) at 38.9% (75/193), compared to PSA and PHI. PHID demonstrated better potential in triaging patients with category 3 lesions, possibly aiding more selective and confident biopsy decisions for csPCa detection, than traditional markers. 4 TECHNICAL EFFICACY: Stage 5.

Implementing consultation audio recording applications to improve informed decision-making (IDM) in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) eligible for docetaxel.

103 Background: Pts with mCRPC have multiple treatment options and face challenges to IDM. This leads some to make poorly informed or goal-discordant decisions. Consultation audio recordings are known to improve IDM by improving recall, but uptake has been limited. It is unclear whether pt-administered apps are an effective, feasible strategy to increase access to recordings and improve IDM. Methods: We conducted a single-site implementation trial. Pts were English-speaking with progressive mCRPC and an upcoming oncology visit in which treatment options including docetaxel would be discussed. Pre-visit, a coordinator sent instructions, provided coaching, and sent text reminders to help pts create recordings using their mobile device. To evaluate change in IDM pre- vs post- the audio-recorded visit, we used an investigator-developed questionnaire testing pt knowledge about docetaxel (19 items, 0-100% correct) and the decisional conflict scale-informed subscale (3 items, 0=feels extremely uninformed to 100=feels extremely informed). Change was evaluated using the Wilcoxon signed-rank test. We also measured implementation: rates of consent, instruction receipt, recording, and listening, as well as pt-reported helpfulness of the app in decision-making. Lastly, we interviewed pts to understand benefits, barriers, and facilitators. Results: Of 78 pts approached, 44 (56%) consented, and 41 (53%) were evaluable. Top reasons for not consenting were too busy (7, 21%), illness (5, 15%), and inadequate devices (4, 12%). Mean age was 75y [56-90], and 34 (83%) were White. Median knowledge about docetaxel increased from 47 to 53 (P=0.048), corresponding to one additional correct response. Median informed subscore increased from 50 to 75 (P=0.011), corresponding to an improvement from feeling neither informed nor uninformed to feeling informed. All pts received instructions, 38 (93%) recorded their visits, and 28 (68%) listened to the recording. Twenty-six pts (63%) found the app helpful in decision-making. In pt interviews, benefits of recording were better recall of treatment options and toxicities, greater decision confidence, and peace of mind. Most frequently reported barriers to use were technology unfamiliarity and disconnected pt portal, telehealth, and recording applications; facilitators were app simplicity and caregiver/coordinator assistance. Conclusions: Implementation of self-administered mobilerecordings was feasible and associated with increased pt knowledge and feeling more informed about treatment with docetaxel in pts with mCRPC. Future efforts should focus on non-White, no/limited-English-speaking populations, and increasing recording/listening rates by addressing barriers and augmenting facilitators (e.g., integrating recordings in electronic pt portals). Clinical trial information: NCT05127850 .

Measures of Patient and Surrogate Preparedness for End-of-Life Decision-Making

ContextReliable and valid measures are critical in accurately assessing outcomes of advance care planning interventions (ACP) for end-of-life (EOL) decision-making. ObjectivesTo develop measures of preparedness for EOL decision-making for patients with end-stage renal disease and their surrogates (an exemplar population). MethodsIn this 3-phase study, Phases 1 and 2 included a cross-discipline concept analysis of the preparedness construct, item generation for patient and surrogate scales (82 items), evaluation of content validity and readability, cognitive interviewing, and item reduction. In phase 3, the retained 26 patient and 25 surrogate items were administered to 426 patients and 426 surrogates during a multisite trial of an ACP intervention versus care-as-usual and evaluated internal consistency, 2-week test-retest reliability, and construct validity. ResultsScales were reduced to 20 patient and 19 surrogate items during phase 3. Cronbach's alphas were 0.86 (patient) and 0.90 (surrogate). There was a strong correlation between preparedness at baseline and two weeks for both scales (r = 0.66–0.69, P < 0.001). Confirmatory factor analysis and item-response analyses suggested unidimensionality. A significant correlation was shown between patient preparedness and patient decisional conflict (r = -0.53, P < 0.001), and surrogate preparedness and surrogate decision-making confidence (r = 0.44, P < 0.001). Among those who received the ACP intervention, the effect size of change was medium: Cohen's d = 0.54, P < 0.001 for patients and d = 0.57, P < 0.001 for surrogates. ConclusionsThe preparedness scales demonstrated strong psychometric properties. Future studies should examine scale performance in other populations.

Cepstral Analysis-Based Artifact Detection, Recognition, and Removal for Prefrontal EEG

This paper proposes to use cepstrum for artifact detection, recognition and removal in prefrontal EEG. This work focuses on the artifact caused by eye movement. A database containing artifact-free EEG and eye movement contaminated EEG from different subjects is established. A cepstral analysis-based feature extraction with support vector machine (SVM) based classifier is designed to identify the artifacts from the target EEG signals. The proposed method achieves an accuracy of 99.62% on the artifact detection task and a 82.79% accuracy on the 6-category eye movement classification task. A statistical value-based artifact removal method is proposed and evaluated on a public EEG database, where an accuracy improvement of 3.46% is obtained on the 3-category emotion classification task. In order to make a confident decision of each 5s EEG segment, the algorithm requires only 0.66M multiplication operations. Compared to the state-of-the-art approaches in artifact detection and removal, the proposed method features higher detection accuracy and lower computational cost, which makes it a more suitable solution to be integrated into a real-time and artifact robust Brain-Machine Interface (BMI).

Effectiveness of an Advance Care Planning Intervention in Adults Receiving Dialysis and Their Families

Evidence of effectiveness of advance care planning (ACP) strategies for patients receiving dialysis and their families is needed. To test the effectiveness of an ACP intervention to prepare patients and their surrogates for end-of-life (EOL) decision-making and to improve surrogate bereavement outcomes. This cluster randomized clinical trial, An Effectiveness-Implementation Trial of SPIRIT (Sharing Patients' Illness Representations to Increase Trust) in ESRD, was conducted from December 2017 to March 2023 and included 42 dialysis clinics in 5 US states (Georgia, New Mexico, North Carolina, Pennsylvania, and Virginia) randomized to provide intervention or usual care. Recruitment was from February 15, 2018, to January 31, 2022, and patient-surrogate dyads were followed up for 21 months (until January 17, 2023) or until patient death. Each clinic selected 1 or 2 health care workers (eg, nurse practitioner, registered nurse, or social worker) to conduct 45- to 60-minute ACP discussions with dyads in the clinic or remotely. After March 13, 2020 (commencement of the COVID-19 emergency declaration), all discussions were conducted remotely. An ACP summary was placed in patients' medical records. The primary, 2-week preparedness outcomes were dyad congruence on EOL goals of care, patient decisional conflict, surrogate decision-making confidence, and a composite of dyad congruence and surrogate decision-making confidence. Secondary bereavement outcomes were anxiety, depression, and posttraumatic distress 3 months after patient death. To adjust for COVID-19 pandemic effects on bereavement outcomes, a variable to indicate the timing of baseline and 3-month assessment relative to the COVID-19 emergency declaration was created. Of the 426 dyads enrolled, 231 were in the intervention clinics, and 195 were in the control clinics. Among all dyads, the mean (SD) patient age was 61.9 (12.7) years, and the mean (SD) surrogate age was 53.7 (15.4) years. At 2 weeks, after adjusting for baseline values, dyad congruence (odds ratio [OR], 1.61; 95% CI, 1.12-2.31; P = .001), decisional conflict scores (β, -0.10; 95% CI, -0.13 to -0.07; P < .001), and the composite (OR, 1.57; 95% CI, 1.06-2.34; P = .03) were higher in the intervention group than in the control group. Surrogate decision-making confidence was similar between groups (β, 0.06; 95% CI, -0.01 to 0.13; P = .12). Among 77 bereaved surrogates, after adjusting for baseline values and assessment timing, intervention group anxiety was lower than control group anxiety (β, -1.55; 95% CI, -3.08 to -0.01; P = .05); however, depression (β, -0.18; 95% CI, -2.09 to 1.73; P = .84) and posttraumatic distress (β, -0.96; 95% CI, -7.39 to 5.46; P = .75) were similar. In this randomized clinical trial, the ACP intervention implemented by health care workers at dialysis centers improved preparation for EOL decision-making but showed mixed effectiveness on bereavement outcomes. The ACP intervention implemented in dialysis centers may be an effective strategy to the dyad preparation for end-of-life care as opposed to the current focus on advance directives. ClinicalTrials.gov Identifier: NCT03138564.

2005 How do emergency ambulance clinicians decide what to do for older adults who have fallen? An analysis of qualitative survey data

Abstract Introduction Around 10% of calls received by English ambulance services are for older adults who have fallen1; with an ageing population there are significant care provision needs. Decision-making on the treatment for people who fall, can impact their future physical and mental health. Previous research in decision-making of ambulance staff found perception of role, confidence, service demands and training to be key drivers2. The previous work highlighting drivers, but not the experiences that explain why they occur, leads this study aim to determine the experiences and confidence of frontline emergency clinicians in attending older adults who have fallen. Method Online cross-sectional survey of frontline emergency clinicians from one English ambulance service in May 2023. Open questions generated qualitative data for thematic analysis3. Ethical and regulatory approvals, and informed consent, were obtained. Results: 81 participants completed the survey. Analysis identified three themes. Care Provision: Provision of hospital avoidance pathways varies throughout the region. Concerns arose from not knowing what different areas had and reduced accessibility out of hours. Communication: Decision-making confidence was impacted by the participants’ experiences; positive experiences encouraged use of hospital avoidance pathways, whilst negative experiences impeded willingness to avoid hospital for fear of repercussion. Shared Decision-Making: Patients, family and clinicians were all valued as part of shared decision-making, with past feedback on decision-making informing future practice. Conclusion Confidence of frontline ambulance staff was impacted by the challenge of a regional and 24/7 ambulance service not having consistent pathways available. This variation led to concerns when responding to patients outside of the clinician’s usual area, and further challenges ambulance clinicians must balance in their practice.

Développement d’un outil d’évaluation de l’anxiété de performance en obstétrique

ObjectiveDeveloping a measuring tool for physician's performance anxiety during obstetrical procedures, as a self-administered questionnaire. MethodsWe used the Delphi method. First, we did a literature review to identify the items to submit for the first round. A panel of experts was asked to rate the relevance of items from one to six. For the first round of Delphi, items were retained if more than 70% of respondents assigned a five or six rating. Items were excluded if more than 70% of respondents assigned a one or two rating. All the other items, plus those suggested by the panel, were submitted to a second round of Delphi. The same item selection conditions were applied to the second round. ResultsThe overall response rate to the Delphi was 79% (19 respondents). At the end of the first round, 14 items were consensually relevant, no item was consensually irrelevant. For the second round, the 18 items that did not find consensus and seven new items suggested by the experts in the first round were submitted. At the end of the second round, nine items were retained by consensus as relevant. ConclusionThis study defined by consensus 23 items for a self-questionnaire to measure specific performance anxiety in obstetrics divided into five dimensions: perceived stress, assessment of the risk of complications, medico-legal risk, impact of the healthcare team and peers, self-confidence and decision-making confidence. We intend to validate this tool in real population.

Improving regulatory efficiency for biotechnology products.

Small procedural changes in how regulatory agencies implement biotech policies can make significant differences in improving regulatory efficiency. This paper discusses how science based, crop specific guidance documents can improve dossier content and the review and approval of biotech varieties. In addition, we describe how the adoption of established risk assessment methodology and applying policy-linked decision making at the agency level can boost both efficiency and developer, public and government confidence in agency decision making and in biotech crops.

Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process

Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction.

“We decided together”: a qualitative study about women with HIV navigating infant-feeding decisions with the father of their children

BackgroundThe World Health Organization (WHO) recommends that women with HIV breastfeed for a minimum of one year. In contrast, United Kingdom (UK) guidelines encourage formula feeding, but breastfeeding can be supported under certain circumstances. Infant-feeding decisions often involve personal and social networks. Currently, little research addresses how individuals with HIV in high-income countries navigate infant-feeding decisions with the father of their children.MethodsSemi-structured remote interviews were conducted with UK-based individuals with a confirmed HIV positive diagnosis who were pregnant or one-year postpartum, and two partners. Using purposive sampling, pregnant and postpartum participants were recruited through HIV NHS clinics and community-based organisations, and where possible, fathers were recruited via them. Data were analysed using thematic analysis and organised using NVivo 12.ResultsOf the 36 women interviewed, 28 were postpartum. The majority were of Black African descent (n = 22) and born outside the UK. The key factors in women navigating HIV and infant-feeding discussions with respect to their baby’s father were the latter’s: (1) awareness of woman’s HIV status; (2) relationship with the woman; (3) confidence in infant-feeding decision; (4) support and opinion about woman’s infant-feeding intentions. Most women made a joint decision with biological fathers when in a long-term (> one year) relationship with them. Single women tended not to discuss their infant-feeding decision with the father of their child, often for safety reasons.ConclusionWomen in ongoing relationships with the father of their child valued their support and opinions regarding infant-feeding. In contrast, single women chose not to involve the father for reasons of privacy and safety. Clinical teams and community-based organisations should support mothers in discussing infant-feeding decisions regardless of relationship status. When appropriate, they should also support discussions with their partners, but remain sensitive to circumstances where this may put women at risk.

Eyecare practitioner perspectives and attitudes towards myopia and myopia management in the UK

ObjectiveMany children with progressive myopia are still prescribed single-vision correction. An investigation into UK eyecare practitioners’ (ECPs) perceptions of myopia management was carried out to ascertain factors which may be...

A portfolio selection using the intuitionistic fuzzy analytic hierarchy process: A case study of the Tehran Stock Exchange

&lt;abstract&gt;&lt;p&gt;In today's economic world, due to the growth of the capital market, the importance for people to invest has increased. The most important concern for investors is choosing the best portfolio for investment. For complex decisions in which the decision maker is ambiguous, such as portfolio selection, using the multi-criteria decision making (MCDM) technique to prioritize options and decide on the optimal choice is the best solution. In this research, a generalization of this method utilizing the intuitionistic fuzzy analytic hierarchy process (IFAHP) was discussed. Considering the importance of this topic in today's economy, the purpose of this research was to describe and apply the new integrated technique of IFAHP for ranking the portfolio of companies admitted to the Tehran Stock Exchange. For this purpose, using the statistics published by the Tehran Stock Exchange, six companies including Jabra Ben Hayyan, Kaghazsazi Kaveh, Laabiran, Daro Luqman, Pashme Shishe Iran, and Bourse Kala Iran were examined. These companies were the best options for investment according to the charts and indices of the stock exchange at the time of our research. Finally, using the technique mentioned above, we described the evaluation and ranking of portfolios for confident and efficient decision -making.&lt;/p&gt;&lt;/abstract&gt;

Bootstrap Inference for Fixed‐Effect Models

The maximum‐likelihood estimator of nonlinear panel data models with fixed effects is asymptotically biased under rectangular‐array asymptotics. The literature has devoted substantial effort to devising methods that correct for this bias as a means to salvage standard inferential procedures. The chief purpose of this paper is to show that the (recursive, parametric) bootstrap replicates the asymptotic distribution of the (uncorrected) maximum‐likelihood estimator and of the likelihood‐ratio statistic. This justifies the use of confidence sets and decision rules for hypothesis testing constructed via conventional bootstrap methods. No modification for the presence of bias needs to be made.

Analisis Efisiensi dDan Keberlanjutan Ekonomi Syariah dalam Konteks Pemilu 2024 di Indonesia: Bibliography Study

This research aims to investigate the impact of the 2024 General Election on Islamic economy in Indonesia using an integrated approach. The primary focus of this study is to develop an analytical model that encompasses economic efficiency, market sentiment, and relevant government policies. By employing sentiment analysis in the market and Islamic investment, the research intends to depict the relationship between public political choices and their effects on market confidence and investment decisions in the Islamic financial sector. Additionally, the study will assess the current government policies' impact on the growth of the Islamic economy and formulate improvement recommendations to support the stability of this sector. Through case studies on Islamic banks undergoing significant changes post-election, the research will deepen the understanding of adaptive operational strategies and their impact on the stability and efficiency of the Islamic financial sector. The results of this research are expected to provide a holistic view of the interconnection between political dynamics, the Islamic economy, and government policies, laying the foundation for the development of sustainable Islamic economic strategies in Indonesia.

Influence of TikTok as an Edutainment Platform on Female Students’ Awareness and Use of Contraceptives

This research study investigates the influence of TikTok, a popular social media platform known for its entertainment and educational content, on the awareness and utilization of contraceptives among female students at Chukwuemeka Odumegwu Ojukwu University (COOU). With the widespread use of social media among the youth, platforms like TikTok have emerged as potential sources of information, creating new opportunities for disseminating knowledge on sensitive topics, such as sexual health and contraception. The main objectives of the study was to evaluate how exposure to contraceptive-related contents on TikTok influence female undergraduates’ awareness and responsible use of contraceptives among COOU female students. The study adopted the uses and gratifications theory in carrying out the study. The survey research method was adopted with a sample size of 400 drawn using Taro Yaame’s formula from a population of 12,552. A structured survey questionnaire is employed to collect data from a representative sample of COOU female students, assessing their knowledge and understanding of contraceptives before and after exposure to contraceptive-related content on TikTok. Preliminary findings indicate that TikTok plays a significant role in increasing the awareness of contraceptive methods among COOU female students. The platform's engaging and informative content fosters an informal learning environment that facilitates discussions around sensitive topics, breaking down barriers and reducing stigmas associated with contraception. Moreover, TikTok's interactive nature allows for peer-to-peer communication, enabling students to share experiences and advice, leading to enhanced knowledge exchange and increased confidence in contraceptive decision-making. The research recommended that TikTok creators should ensure that the information shared on contraceptives is accurate and reliable and partner with experts to add credibility to the content.

Breamy: An augmented reality mHealth prototype for surgical decision-making in breast cancer.

Breast cancer is one of the most prevalent forms of cancer, affecting approximately one in eight women during their lifetime. Deciding on breast cancer treatment, which includes the choice between surgical options, frequently demands prompt decision-making within an 8-week timeframe. However, many women lack the necessary knowledge and preparation for making informed decisions. Anxiety and unsatisfactory outcomes can result from inadequate decision-making processes, leading to decisional regret and revision surgeries. Shared decision-making and personalized decision aids have shown positive effects on patient satisfaction and treatment outcomes. Here, Breamy, a prototype mobile health application that utilizes augmented reality technology to assist breast cancer patients in making more informed decisions is introduced. Breamy provides 3D visualizations of different surgical procedures, aiming to improve confidence in surgical decision-making, reduce decisional regret, and enhance patient well-being after surgery. To determine the perception of the usefulness of Breamy, data was collected from 166 participants through an online survey. The results suggest that Breamy has the potential to reduce patients' anxiety levels and assist them indecision-making.

A semantic fidelity interpretable-assisted decision model for lung nodule classification.

Early diagnosis of lung nodules is important for the treatment of lung cancer patients, existing capsule network-based assisted diagnostic models for lung nodule classification have shown promising prospects in terms of interpretability. However, these models lack the ability to draw features robustly at shallow networks, which in turn limits the performance of the models. Therefore, we propose a semantic fidelity capsule encoding and interpretable (SFCEI)-assisted decision model for lung nodule multi-class classification. First, we propose multilevel receptive field feature encoding block to capture multi-scale features of lung nodules of different sizes. Second, we embed multilevel receptive field feature encoding blocks in the residual code-and-decode attention layer to extract fine-grained context features. Integrating multi-scale features and contextual features to form semantic fidelity lung nodule attribute capsule representations, which consequently enhances the performance of the model. We implemented comprehensive experiments on the dataset (LIDC-IDRI) to validate the superiority of the model. The stratified fivefold cross-validation results show that the accuracy (94.17%) of our method exceeds existing advanced approaches in the multi-class classification of malignancy scores for lung nodules. The experiments confirm that the methodology proposed can effectively capture the multi-scale features and contextual features of lung nodules. It enhances the capability of shallow structure drawing features in capsule networks, which in turn improves the classification performance of malignancy scores. The interpretable model can support the physicians' confidence in clinical decision-making.

Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy

Establishing appropriate trust and maintaining a balanced reliance on digital resources are vital for accurate optical diagnoses and effective integration of computer-aided diagnosis (CADx) in colonoscopy. Active learning using diverse polyp image datasets can help in developing precise CADx systems. Enhancing doctors’ digital literacy and interpreting their results is crucial. Explainable artificial intelligence (AI) addresses opacity, and textual descriptions, along with AI-generated content, deepen the interpretability of AI-based findings by doctors. AI conveying uncertainties and decision confidence aids doctors’ acceptance of results. Optimal AI-doctor collaboration requires improving algorithm performance, transparency, addressing uncertainties, and enhancing doctors’ optical diagnostic skills.