Datas Impact on Algorithmic Bias

Algorithmic bias refers to systematic and structured errors in an artificial intelligence system that generate unfair results and inequalities. This column discusses how bias in algorithms appears, amplifies over time, and shapes peoples thinking, potentially leading to discrimination

Human-Centered AI: A Framework for Green and Sustainable AI

A human-centered artificial intelligence (AI) approach is proposed as a theoretical foundation and a practical guideline to achieve green and sustainable AI. The goal of this study is to contribute to the discussion of AI as both more sustainable and greener

Algorithm awareness: Why user awareness is critical for personal privacy in the adoption of algorithmic platforms?

Understanding how algorithms shape users’ online experiences is a prerequisite to developing an effective algorithm design. Due to the rapid algorithmification of platforms, it is timely to examine users’ awareness of algorithms on online platforms because these algorithms can shape everyday decisions and interactions through mediating, gatekeeping, and structuring user interactions. Focusing on the role of algorithm awareness (AA) in the privacy calculus process, we investigate users’ intention to disclose personal information when using a platform with personalized algorithms. By conceptualizing AA with a range of theoretical and behavioral variables, we examine how users’ self-efficacy affects their privacy concerns when they adopt, consume, and interact with such platforms. The findings show that AA leads users to envisage, understand, and interact with algorithms depending on their understanding of the control of the information flow embedded within them. The awareness that users have regarding algorithms influences the trust of algorithmic processes and the way users evaluate privacy concerns and self-disclosures. The cognitive user processes of AA provide conceptual frameworks for algorithm design and a practical guideline for the design of personalized algorithms

The Nudging Effect of Accuracy Alerts for Combating the Diffusion of Misinformation: Algorithmic News Sources, Trust in Algorithms, and Users’ Discernment of Fake News

Research has revealed that the diffusion of misinformation online can be attributed to inaccuracies in human cognitive reasoning. We examine the nudging effect of Accuracy Alerts on users’ ability to discern misinformation and how their trust moderates this effect. The results from a 2 (accuracy nudge: with nudge vs. no nudge) × 2 (news source type: algorithmic news vs. legacy non-algorithmic news) experiment showed significant main and interaction effects indicating that an algorithmic source effect is present in the process of nudge acceptance. Misinformation sharing intention was largely lower for legacy non-algorithmic news than algorithmic news, but there was a greater decrease in algorithmic news when nudging was employed

Prognostic biomarkers in patients with human immunodeficiency virusâ positive disease with head and neck squamous cell carcinoma

BackgroundWe examined the prognostic value of a panel of biomarkers in patients with squamous cell carcinoma of the head and neck (SCCHN) who were human immunodeficiency virus (HIV) positive (HIVâ positive head and neck cancer) and HIV negative (HIVâ negative head and neck cancer).MethodsTissue microarrays (TMAs) were constructed using tumors from 41 disease siteâ matched and ageâ matched HIVâ positive head and neck cancer cases and 44 HIVâ negative head and neck cancer controls. Expression of tumor biomarkers was assessed by immunohistochemistry (IHC) and correlations examined with clinical variables.ResultsExpression levels of the studied oncogenic and inflammatory tumor biomarkers were not differentially regulated by HIV status. Among patients with HIVâ positive head and neck cancer, laryngeal disease site (P = .003) and Clavienâ Dindo classification IV (CD4) counts <200 cells/μL (P = .01) were associated with poor prognosis. Multivariate analysis showed that p16 positivity was associated with improved overall survival (OS; P < .001) whereas increased expression of transforming growth factorâ beta (TGFâ β) was associated with poor clinical outcome (P = .001).ConclusionDisease site has significant effect on the expression of biomarkers. Expression of tumor TGFâ β could be a valuable addition to the conventional risk stratification equation for improving head and neck cancer disease management strategies.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139994/1/hed24911.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139994/2/hed24911_am.pd

A novel diffuse gastric cancer susceptibility variant in E-cadherin (CDH1) intron 2: A case control study in an Italian population

<p>Abstract</p> <p>Background</p> <p>Inherited genetic factors such as E-cadherin (<it>CDH1</it>) promoter variants are believed to influence the risk towards sporadic diffuse gastric cancer (DGC). Recently, a new regulatory region essential for <it>CDH1 </it>transcription has been identified in <it>CDH1 </it>intron 2.</p> <p>Methods</p> <p>We genotyped all known polymorphisms located within conserved sequences of <it>CDH1 </it>intron 2 (rs10673765, rs9932686, rs1125557, rs9282650, rs9931853) in an Italian population consisting of 134 DGC cases and 100 healthy controls (55 patient relatives and 45 unrelated, matched individuals). The influence of individual variants on DGC risk was assessed using χ²-tests and logistic regression. The relative contribution of alleles was estimated by haplotype analysis.</p> <p>Results</p> <p>We observed a significant (p < 0.0004) association of the <it>CDH1 </it>163+37235G>A variant (rs1125557) with DGC risk. Odds ratios were 4.55 (95%CI = 2.09–9.93) and 1.38 (95%CI = 0.75–2.55) for AA and GA carriers, respectively. When adjusted for age, sex, smoking status, alcohol intake and <it>H. pylori </it>infection, the risk estimates remained largely significant for AA carriers. Haplotype analysis suggested the 163+37235A-allele contributes to disease risk independently of the other variants studied.</p> <p>Conclusion</p> <p>The <it>CDH1 </it>163+37235G>A polymorphism may represent a novel susceptibility variant for sporadic DGC if confirmed in other populations. Considering the broad expression of E-cadherin in epithelia, this exploratory study encourages further evaluation of the 163+37235A-allele as a susceptibility variant in other carcinomas.</p

A Network-Based Approach to Prioritize Results from Genome-Wide Association Studies

Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses

Mortality Among Adults With Cancer Undergoing Chemotherapy or Immunotherapy and Infected With COVID-19

Importance: Large cohorts of patients with active cancers and COVID-19 infection are needed to provide evidence of the association of recent cancer treatment and cancer type with COVID-19 mortality. // Objective: To evaluate whether systemic anticancer treatments (SACTs), tumor subtypes, patient demographic characteristics (age and sex), and comorbidities are associated with COVID-19 mortality. // Design, Setting, and Participants: The UK Coronavirus Cancer Monitoring Project (UKCCMP) is a prospective cohort study conducted at 69 UK cancer hospitals among adult patients (≥18 years) with an active cancer and a clinical diagnosis of COVID-19. Patients registered from March 18 to August 1, 2020, were included in this analysis. // Exposures: SACT, tumor subtype, patient demographic characteristics (eg, age, sex, body mass index, race and ethnicity, smoking history), and comorbidities were investigated. // Main Outcomes and Measures: The primary end point was all-cause mortality within the primary hospitalization. // Results: Overall, 2515 of 2786 patients registered during the study period were included; 1464 (58%) were men; and the median (IQR) age was 72 (62-80) years. The mortality rate was 38% (966 patients). The data suggest an association between higher mortality in patients with hematological malignant neoplasms irrespective of recent SACT, particularly in those with acute leukemias or myelodysplastic syndrome (OR, 2.16; 95% CI, 1.30-3.60) and myeloma or plasmacytoma (OR, 1.53; 95% CI, 1.04-2.26). Lung cancer was also significantly associated with higher COVID-19–related mortality (OR, 1.58; 95% CI, 1.11-2.25). No association between higher mortality and receiving chemotherapy in the 4 weeks before COVID-19 diagnosis was observed after correcting for the crucial confounders of age, sex, and comorbidities. An association between lower mortality and receiving immunotherapy in the 4 weeks before COVID-19 diagnosis was observed (immunotherapy vs no cancer therapy: OR, 0.52; 95% CI, 0.31-0.86). // Conclusions and Relevance: The findings of this study of patients with active cancer suggest that recent SACT is not associated with inferior outcomes from COVID-19 infection. This has relevance for the care of patients with cancer requiring treatment, particularly in countries experiencing an increase in COVID-19 case numbers. Important differences in outcomes among patients with hematological and lung cancers were observed