On the Interdependence of Reliance Behavior and Accuracy in AI-Assisted Decision-Making

In AI-assisted decision-making, a central promise of putting a human in the loop is that they should be able to complement the AI system by adhering to its correct and overriding its mistaken recommendations. In practice, however, we often see that humans tend to over- or under-rely on AI recommendations, meaning that they either adhere to wrong or override correct recommendations. Such reliance behavior is detrimental to decision-making accuracy. In this work, we articulate and analyze the interdependence between reliance behavior and accuracy in AI-assisted decision-making, which has been largely neglected in prior work. We also propose a visual framework to make this interdependence more tangible. This framework helps us interpret and compare empirical findings, as well as obtain a nuanced understanding of the effects of interventions (e.g., explanations) in AI-assisted decision-making. Finally, we infer several interesting properties from the framework: (i) when humans under-rely on AI recommendations, there may be no possibility for them to complement the AI in terms of decision-making accuracy; (ii) when humans cannot discern correct and wrong AI recommendations, no such improvement can be expected either; (iii) interventions may lead to an increase in decision-making accuracy that is solely driven by an increase in humans' adherence to AI recommendations, without any ability to discern correct and wrong. Our work emphasizes the importance of measuring and reporting both effects on accuracy and reliance behavior when empirically assessing interventions.Comment: The Second International Conference on Hybrid Human-Artificial Intelligence (HHAI 2023

Developing a contemporary community clinic for patients with heart failure with preserved ejection fraction within the current National Health Service model

INTRODUCTION: The diagnostic and therapeutic arsenal for heart failure with preserved ejection (HFpEF) has expanded. With novel therapies (eg, sodium-glucose co-transporter 2 inhibitors) and firmer recommendations to optimise non-cardiac comorbidities, it is unclear if outpatient HFpEF models can adequately deliver this. We; therefore, evaluated the efficacy of an existing dedicated HFpEF clinic to find innovative ways to design a more comprehensive model tailored to the modern era of HFpEF. METHODS: A single-centre retrospective analysis of 202 HFpEF outpatients was performed over 12 months before the COVID-19 pandemic. Baseline characteristics, clinic activities (eg, medication changes, lifestyle modifications, management of comorbidities) and follow-up arrangements were compared between a HFpEF and general cardiology clinic to assess their impact on mortality and morbidity at 6 and 12 months. RESULTS: Between the two clinic groups, the sample population was evenly matched with a typical HFpEF profile (mean age 79±9.6 years, 55% female and a high prevalence of cardiometabolic comorbidities). While follow-up practices were similar, the HFpEF clinic delivered significantly more interventions on lifestyle changes, blood pressure and heart rate control (p60% of hospitalisation, including causes of recurrent admissions. CONCLUSION: This study suggests that existing general and emerging dedicated HFpEF clinics may not be adequate in addressing the multifaceted aspects of HFpEF as clinic activities concentrated primarily on cardiological measures. Although the small cohort and short follow-up period are important limitations, this study reminds clinicians that HFpEF patients are more at risk of non-cardiac than HF-related events. We have therefore proposed a pragmatic framework that can comprehensively deliver the modern guideline-directed recommendations and management of non-cardiac comorbidities through a multidisciplinary approach

FACTORS THAT INFLUENCE THE ADOPTION OF HUMAN-AI COLLABORATION IN CLINICAL DECISION-MAKING

Recent developments in Artificial Intelligence (AI) have fueled the emergence of human-AI collaboration, a setting where AI is a coequal partner. Especially in clinical decision-making, it has the potential to improve treatment quality by assisting overworked medical professionals. Even though research has started to investigate the utilization of AI for clinical decision-making, its potential benefits do not imply its adoption by medical professionals. While several studies have started to analyze adoption criteria from a technical perspective, research providing a human-centered perspective with a focus on AI’s potential for becoming a coequal team member in the decision-making process remains limited. Therefore, in this work, we identify factors for the adoption of human-AI collaboration by conducting a series of semi-structured interviews with experts in the healthcare domain. We identify six relevant adoption factors and highlight existing tensions between them and effective human-AI collaboration

Let\u27s Teach Our Students Legal Technology... But What Should We Include?

A renaissance” is often described as a cultural rebirth, a movement ushering in a modern age and leaving behind the old ways of doing things. There is every indication that we are entering a technology-driven renaissance in the legal profession. Artificial intelligence (AI), “big data,” document automation, e-discovery tools, cloud-based case management systems, and communication and collaboration tools are just a few of the ways that technology is transforming the practice of law in the twenty-first century

No association between major depression with and without childhood adversity and the stress hormone copeptin

Background: Adverse childhood experiences (ACE) are associated with an increased risk of major depressive disorder (MDD) and hypothalamic-pituitary-adrenal (HPA) axis dysregulation. Within the HPA axis, corticotropin-releasing hormone and vasopressin (AVP) synergistically stimulate the release of adrenocorticotropic hormone, which promotes cortisol release. The cleavage product copeptin is produced during AVP synthesis and is a surrogate marker of AVP release. Children with ACE and young adults with depressive symptoms have higher levels of copeptin than healthy controls. Objective: To uncover the effects of MDD and ACE on copeptin levels in adult females. Methods: We recruited 94 women (mean age: 34.0 +/- 3.6 years): 23 with MDD and ACE, 24 with MDD without ACE, 22 with ACE without MDD, and 25 healthy controls. ACE was defined as repeated sexual or physical abuse at least once a month over at least one year before the age of 18 years. MDD was defined by the DSM-IV criteria. Copeptin plasma levels were measured with an immunoluminometric assay. Results: The four groups did not differ in demographic variables. We found a significant negative correlation between body mass index (BMI) and copeptin plasma levels (r = -.21; p = .045). Copeptin plasma levels did not differ between the four groups after controlling for BMI. Conclusion: Neither MDD nor ACE was associated with altered plasma copeptin levels. Thus, copeptin does not seem to play a major role in MDD and ACE in adult females

DEPTOR Is an mTOR Inhibitor Frequently Overexpressed in Multiple Myeloma Cells and Required for Their Survival

The mTORC1 and mTORC2 pathways regulate cell growth, proliferation, and survival. We identify DEPTOR as an mTOR-interacting protein whose expression is negatively regulated by mTORC1 and mTORC2. Loss of DEPTOR activates S6K1, Akt, and SGK1, promotes cell growth and survival, and activates mTORC1 and mTORC2 kinase activities. DEPTOR overexpression suppresses S6K1 but, by relieving feedback inhibition from mTORC1 to PI3K signaling, activates Akt. Consistent with many human cancers having activated mTORC1 and mTORC2 pathways, DEPTOR expression is low in most cancers. Surprisingly, DEPTOR is highly overexpressed in a subset of multiple myelomas harboring cyclin D1/D3 or c-MAF/MAFB translocations. In these cells, high DEPTOR expression is necessary to maintain PI3K and Akt activation and a reduction in DEPTOR levels leads to apoptosis. Thus, we identify a novel mTOR-interacting protein whose deregulated overexpression in multiple myeloma cells represents a mechanism for activating PI3K/Akt signaling and promoting cell survival.Howard Hughes Medical Institute (Investigator)Dana-Farber Cancer Institute (High-Tech Research Fund)National Cancer Institute (U.S.)National Institutes of Health (U.S.) (Intramural Research Program)American Cancer SocietyCanadian Institutes of Health Research (Fellowship)American Diabetes Association (Fellowship)W. M. Keck FoundationNational Institutes of Health (U.S.) (R01 CA103866)National Institutes of Health (U.S.) (NIH; R01 AI47389

Paradoxical expression of INK4c in proliferative multiple myeloma tumors: bi-allelic deletion vs increased expression

BACKGROUND: A high proliferative capacity of tumor cells usually is associated with shortened patient survival. Disruption of the RB pathway, which is critically involved in regulating the G1 to S cell cycle transition, is a frequent target of oncogenic events that are thought to contribute to increased proliferation during tumor progression. Previously, we determined that p18INK4c, an essential gene for normal plasma cell differentiation, was bi-allelically deleted in five of sixteen multiple myeloma (MM) cell lines. The present study was undertaken to investigate a possible role of p18INK4c in increased proliferation of myeloma tumors as they progress. RESULTS: Thirteen of 40 (33%) human myeloma cell lines do not express normal p18INK4c, with bi-allelic deletion of p18 in twelve, and expression of a mutated p18 fragment in one. Bi-allelic deletion of p18, which appears to be a late progression event, has a prevalence of about 2% in 261 multiple myeloma (MM) tumors, but the prevalence is 6 to10% in the 50 tumors with a high expression-based proliferation index. Paradoxically, 24 of 40 (60%) MM cell lines, and 30 of 50 (60%) MM tumors with a high proliferation index express an increased level of p18 RNA compared to normal bone marrow plasma cells, whereas this occurs in only five of the 151 (3%) MM tumors with a low proliferation index. Tumor progression is often accompanied by increased p18 expression and an increased proliferation index. Retroviral-mediated expression of exogenous p18 results in marked growth inhibition in three MM cell lines that express little or no endogenous p18, but has no effect in another MM cell line that already expresses a high level of p18. CONCLUSION: Paradoxically, although loss of p18 appears to contribute to increased proliferation of nearly 10% of MM tumors, most MM cell lines and proliferative MM tumors have increased expression of p18. Apart from a small fraction of cell lines and tumors that have inactivated the RB1 protein, it is not yet clear how other MM cell lines and tumors have become insensitive to the anti-proliferative effects of increased p18 expression

Inhibition of Toll-Like Receptor 4 Signaling Mitigates Microvascular Loss but Not Fibrosis in a Model of Ischemic Acute Kidney Injury

The development of chronic kidney disease (CKD) following an episode of acute kidney injury (AKI) is an increasingly recognized clinical problem. Inhibition of toll-like receptor 4 (TLR4) protects renal function in animal models of AKI and has become a viable therapeutic strategy in AKI. However, the impact of TLR4 inhibition on the chronic sequelae of AKI is unknown. Consequently, we examined the chronic effects of TLR4 inhibition in a model of ischemic AKI. Mice with a TLR4-deletion on a C57BL/6 background and wild-type (WT) background control mice (C57BL/6) were subjected to bilateral renal artery clamping for 19 min and reperfusion for up to 6 weeks. Despite the acute protective effect of TLR4 inhibition on renal function (serum creatinine 1.6 ± 0.4 mg/dL TLR4-deletion vs. 2.8 ± 0.3 mg/dL·WT) and rates of tubular apoptosis following ischemic AKI, we found no difference in neutrophil or macrophage infiltration. Furthermore, we observed significant protection from microvascular rarefaction at six weeks following injury with TLR4-deletion, but this did not alter development of fibrosis. In conclusion, we validate the acute protective effect of TLR4 signal inhibition in AKI but demonstrate that this protective effect does not mitigate the sequential fibrogenic response in this model of ischemic AKI