Artificial intelligence technologies and compassion in healthcare: A systematic scoping review

BackgroundAdvances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored.ObjectivesThe aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare?Materials and methodsA systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011–2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice.ResultsSearches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan–Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships.ConclusionThere is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships.ImplicationsIn a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring

Prospectus, November 27, 1985

https://spark.parkland.edu/prospectus_1985/1028/thumbnail.jp

A CDC20-APC/SOX2 Signaling Axis Regulates Human Glioblastoma Stem-like Cells

SummaryGlioblastoma harbors a dynamic subpopulation of glioblastoma stem-like cells (GSCs) that can propagate tumors in vivo and is resistant to standard chemoradiation. Identification of the cell-intrinsic mechanisms governing this clinically important cell state may lead to the discovery of therapeutic strategies for this challenging malignancy. Here, we demonstrate that the mitotic E3 ubiquitin ligase CDC20-anaphase-promoting complex (CDC20-APC) drives invasiveness and self-renewal in patient tumor-derived GSCs. Moreover, CDC20 knockdown inhibited and CDC20 overexpression increased the ability of human GSCs to generate brain tumors in an orthotopic xenograft model in vivo. CDC20-APC control of GSC invasion and self-renewal operates through pluripotency-related transcription factor SOX2. Our results identify a CDC20-APC/SOX2 signaling axis that controls key biological properties of GSCs, with implications for CDC20-APC-targeted strategies in the treatment of glioblastoma

Recall patterns and risk of primary liver cancer for subcentimeter ultrasound liver observations: a multicenter study

BACKGROUND: Patients with cirrhosis and subcentimeter lesions on liver ultrasound are recommended to undergo short-interval follow-up ultrasound because of the presumed low risk of primary liver cancer (PLC). AIMS: The aim of this study is to characterize recall patterns and risk of PLC in patients with subcentimeter liver lesions on ultrasound. METHODS: We conducted a multicenter retrospective cohort study among patients with cirrhosis or chronic hepatitis B infection who had subcentimeter ultrasound lesions between January 2017 and December 2019. We excluded patients with a history of PLC or concomitant lesions ≥1 cm in diameter. We used Kaplan Meier and multivariable Cox regression analyses to characterize time-to-PLC and factors associated with PLC, respectively. RESULTS: Of 746 eligible patients, most (66.0%) had a single observation, and the median diameter was 0.7 cm (interquartile range: 0.5-0.8 cm). Recall strategies varied, with only 27.8% of patients undergoing guideline-concordant ultrasound within 3-6 months. Over a median follow-up of 26 months, 42 patients developed PLC (39 HCC and 3 cholangiocarcinoma), yielding an incidence of 25.7 cases (95% CI, 6.2-47.0) per 1000 person-years, with 3.9% and 6.7% developing PLC at 2 and 3 years, respectively. Factors associated with time-to-PLC were baseline alpha-fetoprotein \u3e10 ng/mL (HR: 4.01, 95% CI, 1.85-8.71), platelet count ≤150 (HR: 4.90, 95% CI, 1.95-12.28), and Child-Pugh B cirrhosis (vs. Child-Pugh A: HR: 2.54, 95% CI, 1.27-5.08). CONCLUSIONS: Recall patterns for patients with subcentimeter liver lesions on ultrasound varied widely. The low risk of PLC in these patients supports short-interval ultrasound in 3-6 months, although diagnostic CT/MRI may be warranted for high-risk subgroups such as those with elevated alpha-fetoprotein levels

Genome-Wide Association Analysis of Ischemic Stroke in Young Adults

Ischemic stroke (IS) is among the leading causes of death in Western countries. There is a significant genetic component to IS susceptibility, especially among young adults. To date, research to identify genetic loci predisposing to stroke has met only with limited success. We performed a genome-wide association (GWA) analysis of early-onset IS to identify potential stroke susceptibility loci. The GWA analysis was conducted by genotyping 1 million SNPs in a biracial population of 889 IS cases and 927 controls, ages 15–49 years. Genotypes were imputed using the HapMap3 reference panel to provide 1.4 million SNPs for analysis. Logistic regression models adjusting for age, recruitment stages, and population structure were used to determine the association of IS with individual SNPs. Although no single SNP reached genome-wide significance (P < 5 × 10−8), we identified two SNPs in chromosome 2q23.3, rs2304556 (in FMNL2; P = 1.2 × 10−7) and rs1986743 (in ARL6IP6; P = 2.7 × 10−7), strongly associated with early-onset stroke. These data suggest that a novel locus on human chromosome 2q23.3 may be associated with IS susceptibility among young adults

Gaze training enhances laparoscopic technical skill acquisition and multi-tasking performance: A randomized, controlled study

Background: The operating room environment is replete with stressors and distractions that increase the attention demands of what are already complex psychomotor procedures. Contemporary research in other fields (e.g., sport) has revealed that gaze training interventions may support the development of robust movement skills. This current study was designed to examine the utility of gaze training for technical laparoscopic skills and to test performance under multitasking conditions. Methods: Thirty medical trainees with no laparoscopic experience were divided randomly into one of three treatment groups: gaze trained (GAZE), movement trained (MOVE), and discovery learning/control (DISCOVERY). Participants were fitted with a Mobile Eye gaze registration system, which measures eye-line of gaze at 25 Hz. Training consisted of ten repetitions of the "eye-hand coordination" task from the LAP Mentor VR laparoscopic surgical simulator while receiving instruction and video feedback (specific to each treatment condition). After training, all participants completed a control test (designed to assess learning) and a multitasking transfer test, in which they completed the procedure while performing a concurrent tone counting task. Results: Not only did the GAZE group learn more quickly than the MOVE and DISCOVERY groups (faster completion times in the control test), but the performance difference was even more pronounced when multitasking. Differences in gaze control (target locking fixations), rather than tool movement measures (tool path length), underpinned this performance advantage for GAZE training. Conclusions: These results suggest that although the GAZE intervention focused on training gaze behavior only, there were indirect benefits for movement behaviors and performance efficiency. Additionally, focusing on a single external target when learning, rather than on complex movement patterns, may have freed-up attentional resources that could be applied to concurrent cognitive tasks. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201