Designing for Appropriate Reliance: The Roles of AI Uncertainty Presentation, Initial User Decision, and User Demographics in AI-Assisted Decision-Making

Appropriate reliance is critical to achieving synergistic human-AI collaboration. For instance, when users over-rely on AI assistance, their human-AI team performance is bounded by the model's capability. This work studies how the presentation of model uncertainty may steer users' decision-making toward fostering appropriate reliance. Our results demonstrate that showing the calibrated model uncertainty alone is inadequate. Rather, calibrating model uncertainty and presenting it in a frequency format allow users to adjust their reliance accordingly and help reduce the effect of confirmation bias on their decisions. Furthermore, the critical nature of our skin cancer screening task skews participants' judgment, causing their reliance to vary depending on their initial decision. Additionally, step-wise multiple regression analyses revealed how user demographics such as age and familiarity with probability and statistics influence human-AI collaborative decision-making. We discuss the potential for model uncertainty presentation, initial user decision, and user demographics to be incorporated in designing personalized AI aids for appropriate reliance.Comment: Accepted to CSCW202

Predicting pragmatic functions of Chinese echo questions using prosody: evidence from acoustic analysis and data modeling

Echo questions serve two pragmatic functions (recapitulatory and explicatory) and are subdivided into two types (yes-no echo question and wh-echo question) in verbal communication. Yet to date, most relevant studies have been conducted in European languages like English and Spanish. It remains unknown whether the different functions of echo questions can be conveyed via prosody in spoken Chinese. Additionally, no comparison was made on the diversified algorithmic models in predicting functions by the prosodity of Chinese echo questions, a novel linguistic cognition in nature. This motivated us to use different acoustic cues to predict different pragmatic functions of Chinese echo questions by virtue of acoustic experiment and data modeling. The results showed that for yes-no echo question, explicatory function exhibited higher pitch and intensity patterns than recapitulatory function whereas for wh-echo question, recapitulatory function demonstrated higher pitch and intensity patterns than explicatory function. With regard to data modeling, the algorithm Support Vector Machine (SVM) relative to Random Forest (RF) and Logistic Regression (LR) performed better when predicting different functions using prosodic cues in both yes-no and wh-echo questions. This study from a digitized perspective adds evidence to the cognition of echo questions’ functions on a prosodic basis

LF-ViT: Reducing Spatial Redundancy in Vision Transformer for Efficient Image Recognition

The Vision Transformer (ViT) excels in accuracy when handling high-resolution images, yet it confronts the challenge of significant spatial redundancy, leading to increased computational and memory requirements. To address this, we present the Localization and Focus Vision Transformer (LF-ViT). This model operates by strategically curtailing computational demands without impinging on performance. In the Localization phase, a reduced-resolution image is processed; if a definitive prediction remains elusive, our pioneering Neighborhood Global Class Attention (NGCA) mechanism is triggered, effectively identifying and spotlighting class-discriminative regions based on initial findings. Subsequently, in the Focus phase, this designated region is used from the original image to enhance recognition. Uniquely, LF-ViT employs consistent parameters across both phases, ensuring seamless end-to-end optimization. Our empirical tests affirm LF-ViT's prowess: it remarkably decreases Deit-S's FLOPs by 63\% and concurrently amplifies throughput twofold. Code of this project is at https://github.com/edgeai1/LF-ViT.git

Campaign-style governance of air pollution in China? A comprehensive analysis of the central environmental protection inspection

Central environmental protection inspection (CEPI) is a major institutional innovation in China's environmental governance, but its effectiveness in improving air quality is still unclear. However, the effectiveness of CEPI is of great significance and can be regarded as an important reference for deepening the reform of environmental governance system in China. This article takes the CEPI as a quasi-natural experiment and uses the regression discontinuity design (RDD) and the difference-in-differences (DID) methods to examine the effectiveness of this policy. The study found that the first round of CEPI reduced the air pollution of cities in the inspected provinces in a short time. Moreover, this positive policy effect persisted in the aftermath of the inspection, but this long-term effect is mainly reflected in PM10 and SO2. Heterogeneity analysis showed that CEPI was only effective in reducing air pollutants of industry-oriented cities, cities in Central and Eastern China, and cities with large or small population size. The moderating effect analysis indicated that a healthy relationship (close and clean) between the local governments and businesses was conducive to reducing air pollution. The research confirmed the presence of “selective” reduction of air pollutants in the long run caused by CEPI, thereby providing new inspiration for the improvement of campaign-style environmental governance and the follow-up CEPI work

A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure

Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break the proximal femur in a particular loading condition. It provides different structural information about the proximal femur that can influence a subject overall fracture risk. To obtain a more robust measure of fracture risk, we used principal component analysis (PCA) to develop a global FEA computed fracture risk index that incorporates the FEA-computed yield and ultimate failure loads and energies to failure in four loading conditions (single-limb stance and impact from a fall onto the posterior, posterolateral, and lateral aspects of the greater trochanter) of 110 hip fracture subjects and 235 age and sex matched control subjects from the AGES-Reykjavik study. We found that the first PC (PC1) of the FE parameters was the only significant predictor of hip fracture. Using a logistic regression model, we determined if prediction performance for hip fracture using PC1 differed from that using FE parameters combined by stratified random resampling with respect to hip fracture status. The results showed that the average of the area under the receive operating characteristic curve (AUC) using PC1 was always higher than that using all FE parameters combined in the male subjects. The AUC of PC1 and AUC of the FE parameters combined were not significantly different than that in the female subjects or in all subjectsComment: 27 pages, 4 figure

Activation of MET signaling by HDAC6 offers a rationale for a novel ricolinostat and crizotinib combinatorial therapeutic strategy in diffuse large B‐cell lymphoma

Some histone deacetylases (HDACs) promote tumor cell growth and pan‐ or selective HDAC inhibitors are active in some cancers; however, the pivotal HDAC enzyme and its functions in human diffuse large B‐cell lymphoma (DLBCL) remain largely unknown. Using NanoString nCounter assays, we profiled HDAC mRNA expression and identified HDAC6 as an upregulated HDAC family member in DLBCL tissue samples. We then found that HDAC6 plays an oncogenic role in DLBCL, as evidenced by its promotion of cell proliferation in vitro and tumor xenograft growth in vivo. Mechanistically, the interaction between HDAC6 and HR23B downregulated HR23B expression, thereby reducing the levels of casitas B‐lineage lymphoma (c‐Cbl), an E3 ubiquitin ligase for hepatocyte growth factor receptor (MET), which resulted in the inhibition of MET ubiquitination‐dependent degradation. In addition, enhanced HDAC6 expression and decreased HR23B expression were correlated with poor overall survival rates among patients with DLBCL. Taken together, these results establish an HDAC6–HR23B–MET axis and indicate that HDAC6 is a potent promoter of lymphomagenesis in DLBCL. Thus, a therapeutic strategy based on HDAC6 inhibitors in combination with MET inhibitors is promising. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146400/1/path5108_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146400/2/path5108.pd

Clinical efficacy of Danshen preparation in the treatment of vascular cognitive impairment: A systematic review and meta-analysis

Ethnopharmacological relevanceDanshen preparations are widely used in the treatment of ischaemic cerebrovascular disease. However, the clinical efficacy of such preparations remains unclear. Consequently, Danshen preparations are used to a lesser extent in vascular cognitive impairment (VCI).Aim of the studyIn this study, we aimed to systematically assess the clinical efficacy and safety of Danshen preparations in VCI. To this end, we examined and performed a meta-analysis (MA) of the evidence available from randomised controlled trials (RCTs) of Danshen preparations conducted in patients with VCI.MethodsWe queried the following sources and collected all articles reporting on RCTs of Danshen preparations published prior to December 2021: PubMed, China National Knowledge Infrastructure (CNKI), Wanfang Data, Chongqing VIP Database (CQVIP), and China Biology Medicine (CBM) disc databases. The assessment of treatments that were included in references were performed by RevMan 5.2 software based on guidelines from Cochrane Handbook for Systematic Reviews of Interventions.ResultsWe included a total of 12 RCTs that included data on clinical therapeutic effects. The evaluation criteria included the following: National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), Barthel Index (BI), Mini-Mental State Assessment (MMSE), Montreal Cognitive Assessment (MOCA), Activities of Daily Living Scale (ADL), treatment effect index, and incidence of adverse reaction index. In the included studies, the observation groups included 656 cases and the control groups included 660 cases. The results of the MA were as follows: the mean difference (MD) value after combining the effect size for NIHSS was −2.91, with a 95% confidence interval (CI) of −4.22 to −1.59; the combined effect quantity hypothesis test revealed that Z = 4.33 (p < 0.00001), indicating that the score pertaining to the degree of neurological deficit (NIHSS) in the observation group after treatment was significantly lower than that in the control group. This result reveals that treatment with a Danshen preparation can reduce neurological deficit in VCI patients. The MD value after combining the effect size for mRS was −0.73, with a 95% CI of −0.85 to −0.61; the result of the combined effect quantity hypothesis test revealed that Z = 12.29 (p < 0.00001). These results indicate that the degree of disability was significantly reduced after treatment in the observation group. The MD value after combining the effect size for MMSE was 2.09, with a 95% CI of 0.33–3.84; the result of the combined effect quantity hypothesis test showed that Z = 2.33 (p = 0.02). These results indicate that the cognitive function score (MMSE) of the observation group after treatment was significantly higher than that of the control group and suggests that the cognitive function of VCI patients was improved after treatment with Danshen preparations. The MD value after combining the effect size for ADL was 8.79, with a 95% CI of 3.52 to 14.06; the result of the combined effect quantity hypothesis test indicated that Z = 3.27 (p = 0.001). These results showed that the life ability (ADL scale) scores of patients in the observation group after treatment were significantly higher than those in the control group, and reveals that after treatment with Danshen preparations, patients exhibited significant improvement in life ability. The MD value after combining the effect size for high-sensitivity C-reactive protein (hs-CRP) was −3.21, with a 95% CI of −4.21 to −2.22; the result of the combined effect quantity hypothesis test showed that Z = 6.31 (p < 0.00001), indicating that the hs-CRP level in the observation group was significantly decreased after treatment. The MD value after combining the effect size for interleukin (IL)-6 was −2.95, with a 95% CI of −3.86 to −2.04; the result of the combined effect quantity hypothesis test showed that Z = 6.36 (p < 0.00001). These results showed that the IL-6 level in the observation group was significantly decreased after treatment.ConclusionThe existing clinical evidence shows that Danshen preparations exert significant therapeutic effects on VCI patients and can ameliorate inflammatory conditions in these patients. In addition, Danshen preparations are relatively safe

Influence of Different Age Cutoff Points on the Prediction of Prognosis of Cancer Patients Receiving ICIs and Potential Mechanistic Exploration

Age is a potential predictive marker for the prognosis of cancer patients treated with immune checkpoint inhibitors (ICIs), but the appropriate age cutoff point is still controversial. We aimed to explore the influence of different age cutoff points on the prediction of prognosis for patients receiving ICIs and explore the mechanism underlying the appropriate age cutoff point from the aspects of gene mutation and expression, immune cell infiltration and so on. We applied cutoff points of 50, 55, 60, 65, 70, and 75 years old to divide 1660 patients from the Memorial Sloan-Kettering Cancer Center (MSKCC) immunotherapy cohort into older and younger groups and performed survival analysis of the six subgroups. The results showed that older patients had better survival than younger patients in accordance with the cutoff point of 50 years old [median overall survival (OS) (95% CI): 13.0 (10.5-15.5) months vs. 20.0 (16.7-23.3) months; p=0.002; unadjusted hazard ratio (HR) (95% CI): 0.77 (0.65-0.91)], whereas no significant difference was observed with other cutoff points. Further analysis of The Cancer Genome Atlas (TCGA) database and the MSKCC immunotherapy cohort data showed that the tumor mutation burden (TMB), neoantigen load (NAL), DNA damage response and repair (DDR) pathway mutation status, mutation frequencies of most genes (except IDH1, BRAF and ATRX), the expression of most immune-related genes and the degree of infiltration of most immune cells (such as CD8+ T cells and M1 macrophages) were higher in the elderly group (aged ≥50 years)

Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics

Background: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing (WGS) data with metabolomics data has emerged as a promising approach to enhance the accuracy of data imputation in metabolomics studies. Method: In this study, we propose a novel method that leverages the information from WGS data and reference metabolites to impute unknown metabolites. Our approach utilizes a multi-view variational autoencoder to jointly model the burden score, polygenetic risk score (PGS), and linkage disequilibrium (LD) pruned single nucleotide polymorphisms (SNPs) for feature extraction and missing metabolomics data imputation. By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information. Results: We evaluate the performance of our method on empirical metabolomics datasets with missing values and demonstrate its superiority compared to conventional imputation techniques. Using 35 template metabolites derived burden scores, PGS and LD-pruned SNPs, the proposed methods achieved R^2-scores > 0.01 for 71.55% of metabolites. Conclusion: The integration of WGS data in metabolomics imputation not only improves data completeness but also enhances downstream analyses, paving the way for more comprehensive and accurate investigations of metabolic pathways and disease associations. Our findings offer valuable insights into the potential benefits of utilizing WGS data for metabolomics data imputation and underscore the importance of leveraging multi-modal data integration in precision medicine research.Comment: 19 pages, 3 figure

Activation of the DDR Pathway Leads to the Down-Regulation of the TGFβ Pathway and a Better Response to ICIs in Patients With Metastatic Urothelial Carcinoma

Immune checkpoint inhibitors (ICIs) have changed the treatment paradigm of metastatic urothelial carcinoma (mUC), a dominant type of bladder cancer (BC). Previous studies have shown an association between gene mutations in the DNA damage response (DDR) pathway and the immunotherapy response in mUC but have neglected the effect of the activation level of the DDR pathway on the ICI response in mUC. A published immunotherapy cohort with genome, transcriptome and survival data for 348 mUC patients was used. An external cohort (The Cancer Genome Atlas Bladder Cancer) and the GSE78220 cohort were used for validation. The activation level of the DDR pathway was quantified using single-sample gene set enrichment analysis (ssGSEA). Further analysis on the genome, immunogenicity, and the immune microenvironment was conducted using the DDR ssGSEA enrichment score-high (DSSH) group and the DDR ssGSEA enrichment score-low (DSSL) group. In the mUC cohorts, the DSSH group was associated with longer overall survival times (P=0.026; Hazard ratio=0.67; 95%CI: 0.46−0.95). The DSSH group was also associated with higher tumor mutation burden, neoantigen load, immune-activated cell patterns, and immune-related gene expression levels. The GSEA results indicated an immune activation state in DSSH group, which correlated with a down-regulation in the transforming growth factor β receptor signaling pathway. Our study suggests that the activation level of the DDR pathway may be a novel predictive marker for immunotherapy efficacy in patients with mUC