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  1. Article: [Besprechung von:] The economics of Australian industry. Ed. by Alex Hunter. Melbourne 1963

    Henderson, R. F

    The economic record : er , p. 101-113

    1964  , Page(s) 101–113

    Author's details R. F. Henderson
    Keywords Industrie ; Australien
    Publisher Blackwell Publ. Asia
    Publishing place Carlton South, Vic.
    Document type Article
    ZDB-ID 203689-7
    Database ECONomics Information System

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  2. Article ; Online: Weakly supervised anomaly detection coupled with Fourier transform infrared (FT-IR) spectroscopy for the identification of non-normal tissue.

    Ferguson, Dougal / Henderson, Alex / McInnes, Elizabeth F / Gardner, Peter

    The Analyst

    2023  Volume 148, Issue 16, Page(s) 3817–3826

    Abstract: The detection and classification of histopathological abnormal tissue constituents using machine learning (ML) techniques generally requires example data for each tissue or cell type of interest. This creates problems for studies on tissue that will have ...

    Abstract The detection and classification of histopathological abnormal tissue constituents using machine learning (ML) techniques generally requires example data for each tissue or cell type of interest. This creates problems for studies on tissue that will have few regions of interest, or for those looking to identify and classify diseases of rarity, resulting in inadequate sample sizes from which to build multivariate and ML models. Regarding the impact on vibrational spectroscopy, specifically infrared (IR) spectroscopy, low numbers of samples may result in ineffective modelling of the chemical composition of sample groups, resulting in detection and classification errors. Anomaly detection may be a solution to this problem, enabling users to effectively model tissue constituents considered to represent normal tissue to capture any abnormal tissue and identify instances of non-normal tissue, be it disease or spectral artefacts. This work illustrates how a novel approach using a weakly supervised anomaly detection algorithm paired with IR microscopy can detect non-normal tissue spectra. In addition to incidental interferents such as hair, dust, and tissue scratches, the algorithm can also detect regions of diseased tissue. The model is never introduced to instances of these groups, training solely on healthy control data using only the IR spectral fingerprint region. This approach is demonstrated using liver tissue data from an agrochemical exposure mouse study.
    MeSH term(s) Mice ; Animals ; Spectroscopy, Fourier Transform Infrared/methods ; Fourier Analysis ; Algorithms ; Hair
    Language English
    Publishing date 2023-08-07
    Publishing country England
    Document type Journal Article
    ZDB-ID 210747-8
    ISSN 1364-5528 ; 0003-2654
    ISSN (online) 1364-5528
    ISSN 0003-2654
    DOI 10.1039/d3an00618b
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2423: Show issues Location:
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  3. Article ; Online: Internal Medicine Resident Barriers to Advance Care Planning in the Primary Care Continuity Clinic.

    Dussault, Nicole / Nickolopoulos, Elissa / Henderson, Katherine / Hemming, Patrick / Cho, Alex / Ma, Jessica E

    The American journal of hospice & palliative care

    2023  Volume 40, Issue 11, Page(s) 1205–1211

    Abstract: ... ...

    Abstract Background
    MeSH term(s) Humans ; Advance Care Planning ; Internal Medicine/education ; Internship and Residency ; Outpatients ; Continuity of Patient Care
    Language English
    Publishing date 2023-02-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1074344-3
    ISSN 1938-2715 ; 1049-9091
    ISSN (online) 1938-2715
    ISSN 1049-9091
    DOI 10.1177/10499091231154606
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.B 3090: Show issues Location:
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  4. Article ; Online: Editorial Commentary.

    Henderson, Alex A / Murray, Katie S

    Urology practice

    2018  Volume 6, Issue 1, Page(s) 51

    Language English
    Publishing date 2018-12-27
    Publishing country United States
    Document type Journal Article
    ISSN 2352-0787
    ISSN (online) 2352-0787
    DOI 10.1097/01.UPJ.0000552860.86285.a3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Exploring AdaBoost and Random Forests machine learning approaches for infrared pathology on unbalanced data sets.

    Tang, Jiayi / Henderson, Alex / Gardner, Peter

    The Analyst

    2021  Volume 146, Issue 19, Page(s) 5880–5891

    Abstract: The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build ... ...

    Abstract The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build chemometric models that can provide objective metrics of disease state. It is important to build robust and stable models to provide confidence to the end user. The data used to develop such models can have a variety of characteristics which can pose problems to many model-building approaches. Here we have compared the performance of two machine learning algorithms - AdaBoost and Random Forests - on a variety of non-uniform data sets. Using samples of breast cancer tissue, we devised a range of training data capable of describing the problem space. Models were constructed from these training sets and their characteristics compared. In terms of separating infrared spectra of cancerous epithelium tissue from normal-associated tissue on the tissue microarray, both AdaBoost and Random Forests algorithms were shown to give excellent classification performance (over 95% accuracy) in this study. AdaBoost models were more robust when datasets with large imbalance were provided. The outcomes of this work are a measure of classification accuracy as a function of training data available, and a clear recommendation for choice of machine learning approach.
    MeSH term(s) Algorithms ; Machine Learning
    Language English
    Publishing date 2021-09-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 210747-8
    ISSN 1364-5528 ; 0003-2654
    ISSN (online) 1364-5528
    ISSN 0003-2654
    DOI 10.1039/d0an02155e
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Importance of Assessing Wellbeing for United States Preventive Services Task Force Recommendations.

    Silverstein, Michael / Kemper, Alex R / Henderson, Jillian T / Mabry-Hernandez, Iris

    Pediatrics

    2021  Volume 148, Issue Suppl 1, Page(s) s37–s39

    MeSH term(s) Adolescent ; Adolescent Health/standards ; Advisory Committees/standards ; Child ; Child Health/standards ; Education ; Evidence-Based Medicine/methods ; Evidence-Based Medicine/standards ; Humans ; Preventive Health Services/methods ; Preventive Health Services/standards ; United States
    Language English
    Publishing date 2021-07-01
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 207677-9
    ISSN 1098-4275 ; 0031-4005
    ISSN (online) 1098-4275
    ISSN 0031-4005
    DOI 10.1542/peds.2021-050693H
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.MO 357: Show issues

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  7. Article ; Online: Associations between eating behaviors and metabolic syndrome severity in young adults.

    Graybeal, Austin J / Brandner, Caleb F / Henderson, Alex / Aultman, Ryan A / Vallecillo-Bustos, Anabelle / Newsome, Ta'Quoris A / Stanfield, Diavion / Stavres, Jon

    Eating behaviors

    2023  Volume 51, Page(s) 101821

    Abstract: Metabolic syndrome (MetS), a precursor to cardiovascular disease and type II diabetes, is rapidly increasing in young adults. Accordingly, earlier interventions aimed at combating the onset of MetS in young adults are required. However, current ... ...

    Abstract Metabolic syndrome (MetS), a precursor to cardiovascular disease and type II diabetes, is rapidly increasing in young adults. Accordingly, earlier interventions aimed at combating the onset of MetS in young adults are required. However, current behavioral interventions have failed to consider the eating behaviors that precede disease development, likely contributing to the consistently high failure rates of these interventions. The purpose of this cross-sectional study was to evaluate the associations between eating behaviors and MetS severity (MetS
    MeSH term(s) Male ; Humans ; Young Adult ; Female ; Adolescent ; Adult ; Metabolic Syndrome ; Diabetes Mellitus, Type 2 ; Cross-Sectional Studies ; Feeding Behavior ; Surveys and Questionnaires
    Language English
    Publishing date 2023-10-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2073366-5
    ISSN 1873-7358 ; 1471-0153
    ISSN (online) 1873-7358
    ISSN 1471-0153
    DOI 10.1016/j.eatbeh.2023.101821
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 6208: Show issues Location:
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  8. Article: Incidence of Spontaneous Pulmonary AVM Rupture in HHT Patients.

    Fish, Adam / Henderson, Katharine / Moushey, Alex / Pollak, Jeffrey / Schlachter, Todd

    Journal of clinical medicine

    2021  Volume 10, Issue 20

    Abstract: The spontaneous rupture of pulmonary AVMs, resulting in pulmonary hemorrhage and hydrothorax, is a life-threatening complication. While this phenomenon has been previously reported, the true incidence is not yet known. This study retrospectively reviewed ...

    Abstract The spontaneous rupture of pulmonary AVMs, resulting in pulmonary hemorrhage and hydrothorax, is a life-threatening complication. While this phenomenon has been previously reported, the true incidence is not yet known. This study retrospectively reviewed records of 801 HHT patients with pulmonary AVMs to identify a single lifetime episode of hemothorax or pulmonary hemorrhage secondary to pulmonary AVM rupture. The lifetime prevalence and incidence of pulmonary AVM rupture in HHT patients was 2.7% and 0.16% respectively. In these patients, AVM rupture represented the initial presentation of HHT in nine (40.9%) cases and was life-threatening in nine (40.9%) cases. All cases occurred in virgin lesions, and subsequent embolization was curative. While a feared complication, pulmonary AVM rupture is rare and is likely effectively prevented by existing embolization techniques and indications.
    Language English
    Publishing date 2021-10-14
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662592-1
    ISSN 2077-0383
    ISSN 2077-0383
    DOI 10.3390/jcm10204714
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Healthcare professionals lack confidence and training in approaching advanced care planning discussions during renal inpatient admissions.

    Anwari, Kashif / Hamilton-Shield, Antonia / Lawal, Abdul Azeez / Henderson, Scott / Burns, Áine / Riding, Alex / Wilson, Jo

    Future healthcare journal

    2022  Volume 9, Issue Suppl 2, Page(s) 59

    Language English
    Publishing date 2022-10-13
    Publishing country England
    Document type Journal Article
    ZDB-ID 3016427-8
    ISSN 2514-6653 ; 2514-6645
    ISSN (online) 2514-6653
    ISSN 2514-6645
    DOI 10.7861/fhj.9-2-s59
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Infrared micro-spectroscopy coupled with multivariate and machine learning techniques for cancer classification in tissue: a comparison of classification method, performance, and pre-processing technique.

    Ferguson, Dougal / Henderson, Alex / McInnes, Elizabeth F / Lind, Rob / Wildenhain, Jan / Gardner, Peter

    The Analyst

    2022  Volume 147, Issue 16, Page(s) 3709–3722

    Abstract: The visual detection, classification, and differentiation of cancers within tissues of clinical patients is an extremely difficult and time-consuming process with severe diagnosis implications. To this end, many computational approaches have been ... ...

    Abstract The visual detection, classification, and differentiation of cancers within tissues of clinical patients is an extremely difficult and time-consuming process with severe diagnosis implications. To this end, many computational approaches have been developed to analyse tissue samples to supplement histological cancer diagnoses. One approach is the interrogation of the chemical composition of the actual tissue samples through the utilisation of vibrational spectroscopy, specifically Infrared (IR) spectroscopy. Cancerous tissue can be detected by analysing the molecular vibration patterns of tissues undergoing IR irradiation, and even graded, with multivariate and Machine Learning (ML) techniques. This publication serves to review and highlight the potential for the application of infrared microscopy techniques such as Fourier Transform Infrared Spectroscopy (FTIR) and Quantum Cascade Laser Infrared Spectroscopy (QCL), as a means to improve diagnostic accuracy and allow earlier detection of human neoplastic disease. This review provides an overview of the detection and classification of different cancerous tissues using FTIR spectroscopy paired with multivariate and ML techniques, using the F1-Score as a quantitative metric for direct comparison of model performances. Comparisons also extend to data handling techniques, with a provision of a suggested pre-processing protocol for future studies alongside suggestions as to reporting standards for future publication.
    MeSH term(s) Humans ; Lasers, Semiconductor ; Machine Learning ; Microscopy/methods ; Neoplasms/diagnosis ; Spectroscopy, Fourier Transform Infrared/methods ; Vibration
    Language English
    Publishing date 2022-08-08
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 210747-8
    ISSN 1364-5528 ; 0003-2654
    ISSN (online) 1364-5528
    ISSN 0003-2654
    DOI 10.1039/d2an00775d
    Database MEDical Literature Analysis and Retrieval System OnLINE

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