455 research outputs found

    Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

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    This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support "Learning Health Systems" with them. Initially, the authors elaborate on these challenges after separating them according to their mitigation strategies: those that need innovative approaches, time, or future technological capabilities and those that require a conceptual reappraisal from a critical perspective. Then, a novel opportunity to support "Learning Health Systems" by integrating hidden information extracted by ML models from digitalized histopathology slides with other healthcare big data is presented

    Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review

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    Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was to assess the performance of externally validated ML models based on histopathology images for diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer. A systematic search of MEDLINE, EMBASE, CINAHL, IEEE, MICCAI, and SPIE conferences was performed for studies published between January 2010 and February 2022. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed, and the results were narratively described. Of the 2011 non-duplicated citations, 8 journal articles and 2 conference proceedings met inclusion criteria. Three studies externally validated ML models for diagnosis, 4 for classification, 2 for prognosis, and 1 for both classification and prognosis. Most studies used Convolutional Neural Networks and one used logistic regression algorithms. For diagnostic/classification models, the most common performance metrics reported in the EV were accuracy and area under the curve, which were greater than 87% and 90%, respectively, using pathologists' annotations as ground truth. The hazard ratios in the EV of prognostic ML models were between 1.7 (95% CI, 1.2-2.6) and 1.8 (95% CI, 1.3-2.7) to predict distant disease-free survival; 1.91 (95% CI, 1.11-3.29) for recurrence, and between 0.09 (95% CI, 0.01-0.70) and 0.65 (95% CI, 0.43-0.98) for overall survival, using clinical data as ground truth. Despite EV being an important step before the clinical application of a ML model, it hasn't been performed routinely. The large variability in the training/validation datasets, methods, performance metrics, and reported information limited the comparison of the models and the analysis of their results (...

    Consensus recommendations for mrd testing in adult b-cell acute lymphoblastic leukemia in ontario

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    Measurable (minimal) residual disease (MRD) is an established, key prognostic factor in adult B-cell acute lymphoblastic leukemia (B-ALL), and testing for MRD is known to be an important tool to help guide treatment decisions. The clinical value of MRD testing depends on the accuracy and reliability of results. Currently, there are no Canadian provincial or national guidelines for MRD testing in adult B-ALL, and consistent with the absence of such guidelines, there is no uniform Ontario MRD testing consensus. Moreover, there is great variability in Ontario in MRD testing with respect to where, when, and by which technique, MRD testing is performed, as well as in how the results are interpreted. To address these deficiencies, an expert multidisciplinary working group was convened to define consensus recommendations for improving the provision of such testing. The expert panel recommends that MRD testing should be implemented in a centralized manner to ensure expertise and accuracy in testing for this low volume indication, thereby to provide accurate, reliable results to clinicians and patients. All adult patients with B-ALL should receive MRD testing after induction chemotherapy. Philadelphia chromosome (Ph)-positive patients should have ongoing monitoring of MRD during treatment and thereafter, while samples from Ph-negative B-ALL patients should be tested at least once later during treatment, ideally at 12 to 16 weeks after treatment initiation. In Ph-negative adult B-ALL patients, standardized, ideally centralized, protocols must be used for MRD testing, including both flow cytometry and immunoglobulin (Ig) heavy chain and T-cell receptor (TCR) gene rearrangement analysis. For Ph-positive B-ALL patients, MRD testing using a standardized protocol for reverse transcription real-time quantitative PCR (RT-qPCR) for the BCR-ABL1 gene fusion transcript is recommended, with Ig/TCR gene rearrangement analysis done in parallel likely providing additional clinical information

    "More money for health - more health for the money": a human resources for health perspective

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    <p>Abstract</p> <p>Background</p> <p>At the MDG Summit in September 2010, the UN Secretary-General launched the Global Strategy for Women's and Children's Health. Central within the Global Strategy are the ambitions of "more money for health" and "more health for the money". These aim to leverage more resources for health financing whilst simultaneously generating more results from existing resources - core tenets of public expenditure management and governance. This paper considers these ambitions from a human resources for health (HRH) perspective.</p> <p>Methods</p> <p>Using data from the UK Department for International Development (DFID) we set out to quantify and qualify the British government's contributions on HRH in developing countries and to establish a baseline.. To determine whether activities and financing could be included in the categorisation of 'HRH strengthening' we adopted the Agenda for Global Action on HRH and a WHO approach to the 'working lifespan' of health workers as our guiding frameworks. To establish a baseline we reviewed available data on Official Development Assistance (ODA) and country reports, undertook a new survey of HRH programming and sought information from multilateral partners.</p> <p>Results</p> <p>In financial year 2008/9 DFID spent ÂŁ901 million on direct 'aid to health'. Due to the nature of the Creditor Reporting System (CRS) of the Organisation for Economic Co-operation and Development (OECD) it is not feasible to directly report on HRH spending. We therefore employed a process of imputed percentages supported by detailed assessment in twelve countries. This followed the model adopted by the G8 to estimate ODA on maternal, newborn and child health. Using the G8's model, and cognisant of its limitations, we concluded that UK 'aid to health' on HRH strengthening is approximately 25%.</p> <p>Conclusions</p> <p>In quantifying DFID's disbursements on HRH we encountered the constraints of the current CRS framework. This limits standardised measurement of ODA on HRH. This is a governance issue that will benefit from further analysis within more comprehensive programmes of workforce science, surveillance and strategic intelligence. The Commission on Information and Accountability for Women's and Children's Health may present an opportunity to partially address the limitations in reporting on ODA for HRH and present solutions to establish a global baseline.</p

    Humanized zebrafish enhance human hematopoietic stem cell survival and promote acute myeloid leukemia clonal diversity

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    Xenograft models are invaluable tools in establishing the current paradigms of hematopoiesis and leukemogenesis. The zebrafish has emerged as a robust alternative xenograft model but, like mice, lack specific cytokines that mimic the microenvironment found in human patients. To address this critical gap, we generated the first humanized zebrafish that express human hematopoietic-specific cytokines (GM-CSF, SCF, and SDF1Îą). Termed GSS fish, these zebrafish promote survival, self-renewal and multilineage differentiation of human hematopoietic stem and progenitor cells and result in enhanced proliferation and hematopoietic niche-specific homing of primary human leukemia cells. Using error-corrected RNA sequencing, we determined that patient-derived leukemias transplanted into GSS zebrafish exhibit broader clonal representation compared to transplants into control hosts. GSS zebrafish incorporating error-corrected RNA sequencing establish a new standard for zebrafish xenotransplantation that more accurately recapitulates the human context, providing a more representative cost-effective preclinical model system for evaluating personalized response-based treatment in leukemia and therapies to expand human hematopoietic stem and progenitor cells in the transplant setting

    The context, influences and challenges for undergraduate nurse clinical education: Continuing the dialogue

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    Introduction – Approaches to clinical education are highly diverse and becoming increasingly complex to sustain in complex milieu Objective – To identify the influences and challenges of providing nurse clinical education in the undergraduate setting and to illustrate emerging solutions. Method: A discursive exploration into the broad and varied body of evidence including peer reviewed and grey literature. Discussion - Internationally, enabling undergraduate clinical learning opportunities faces a range of challenges. These can be illustrated under two broad themes: (1) Legacies from the past and the inherent features of nurse education and (2) Challenges of the present, including, population changes, workforce changes, and the disconnection between the health and education sectors. Responses to these challenges are triggering the emergence of novel approaches, such as collaborative models. Conclusion(s) – Ongoing challenges in providing accessible, effective and quality clinical learning experiences are apparent

    Job Embeddedness Demonstrates Incremental Validity When Predicting Turnover Intentions for Australian University Employees

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    Job embeddedness is a construct that describes the manner in which employees can be enmeshed in their jobs, reducing their turnover intentions. Recent questions regarding the properties of quantitative job embeddedness measures, and their predictive utility, have been raised. Our study compared two competing reflective measures of job embeddedness, examining their convergent, criterion, and incremental validity, as a means of addressing these questions. Cross-sectional quantitative data from 246 Australian university employees (146 academic; 100 professional) was gathered. Our findings indicated that the two compared measures of job embeddedness were convergent when total scale scores were examined. Additionally, job embeddedness was capable of demonstrating criterion and incremental validity, predicting unique variance in turnover intention. However, this finding was not readily apparent with one of the compared job embeddedness measures, which demonstrated comparatively weaker evidence of validity. We discuss the theoretical and applied implications of these findings, noting that job embeddedness has a complementary place among established determinants of turnover intention

    Potential of dynamic ocean management strategies for western Pacific leatherback sea turtle bycatch mitigation in New Zealand

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    Western Pacific leatherback sea turtles (Dermochelys coriacea) are a priority bycatch mitigation concern due to the projected extinction of the population before the end of the 21st century. The species regularly occurs as bycatch in gillnet and surface longline fisheries. Here, we explore the potential for dynamic ocean management in an emerging hotspot of leatherback sea turtle bycatch in the New Zealand pelagic longline fishery. We compared spatial areas of different sizes built from single oceanographic covariates as well as built from a composite risk surface developed through ensemble random forests. We found that, individually, the Okubo–Weiss parameter, sea surface temperature (SST) anomaly, SST, moon phase, and distance to the SST front were important oceanographic covariates for leatherback sea turtle bycatch. However, the spatial areas built from the composite risk surface were the most effective at discriminating sets with and without bycatch across a range of risk cutoffs. When we also considered implementation metrics of spatial area and coherence as part of performance, the area derived from the composite risk surface with a risk of interaction per set greater than 52% performed best. This spatial area was ephemeral, occurring 1 or 2 weeks each year, and localized, occurring along the north coast of East Cape in the North Island of New Zealand. The apparent presence of discrete spatial areas with elevated risk may be useful to inform future management in the area. Considering implementation metrics in defining utility was useful for identifying tradeoffs between the total size and the underlying covariates delineating a spatial area. As such, we recommend these types of metrics to be included when designing spatial bycatch mitigation strategies elsewhere
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