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  1. Article ; Online: Erratum to: The Development and Validation of Artificial Intelligence Pediatric Appendicitis Decision-Tree for Children 0 to 12 Years Old.

    Shikha, Anas / Kasem, Asem

    European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie

    2023  Volume 33, Issue 5, Page(s) e1

    Language English
    Publishing date 2023-11-10
    Publishing country United States
    Document type Journal Article ; Published Erratum
    ZDB-ID 1065043-x
    ISSN 1439-359X ; 0939-7248 ; 0939-6764 ; 0930-7249
    ISSN (online) 1439-359X
    ISSN 0939-7248 ; 0939-6764 ; 0930-7249
    DOI 10.1055/s-0043-1776976
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3140: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  2. Article ; Online: The Development and Validation of Artificial Intelligence Pediatric Appendicitis Decision-Tree for Children 0 to 12 Years Old.

    Shikha, Anas / Kasem, Asem

    European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie

    2022  Volume 33, Issue 5, Page(s) 395–402

    Abstract: Introduction:  Diagnosing appendicitis in young children (0-12 years) still poses a special difficulty despite the advent of radiological investigations. Few scoring models have evolved and been applied worldwide, but with significant fluctuations in ... ...

    Abstract Introduction:  Diagnosing appendicitis in young children (0-12 years) still poses a special difficulty despite the advent of radiological investigations. Few scoring models have evolved and been applied worldwide, but with significant fluctuations in accuracy upon validation.
    Aim:  To utilize artificial intelligence (AI) techniques to develop and validate a diagnostic model based on clinical and laboratory parameters only (without imaging), in addition to prospective validation to confirm the findings.
    Methods:  In Stage-I, observational data of children (0-12 years), referred for acute appendicitis (March 1, 2016-February 28, 2019,
    Results:  The developed model, AI Pediatric Appendicitis Decision-tree (AiPAD), is both accurate and explainable, with an XV estimation of average accuracy to be 93.5% ± 5.8 (91.4% positive predictive value [PPV] and 94.8% negative predictive value [NPV]). Prospective validation revealed that the model was indeed accurate and close to the XV evaluations, with an overall accuracy of 97.1% (96.7% PPV and 97.4% NPV).
    Conclusion:  The AiPAD is validated, highly accurate, easy to comprehend, and offers an invaluable tool to use in diagnosing appendicitis in children without the need for imaging. Ultimately, this would lead to significant practical benefits, improved outcomes, and reduced costs.
    MeSH term(s) Child ; Humans ; Child, Preschool ; Infant, Newborn ; Infant ; Appendicitis/diagnostic imaging ; Appendicitis/surgery ; Artificial Intelligence ; Predictive Value of Tests ; Acute Disease ; Decision Trees ; Sensitivity and Specificity
    Language English
    Publishing date 2022-09-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1065043-x
    ISSN 1439-359X ; 0939-7248 ; 0939-6764 ; 0930-7249
    ISSN (online) 1439-359X
    ISSN 0939-7248 ; 0939-6764 ; 0930-7249
    DOI 10.1055/a-1946-0157
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3140: Show issues Location:
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  3. Article: Erratum to: The Development and Validation of Artificial Intelligence Pediatric Appendicitis Decision-Tree for Children 0 to 12 Years Old

    Shikha, Anas / Kasem, Asem

    European Journal of Pediatric Surgery

    2023  Volume 33, Issue 05, Page(s) e1–e1

    Language English
    Publishing date 2023-10-01
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article
    ZDB-ID 1065043-x
    ISSN 1439-359X ; 0939-7248 ; 0939-6764 ; 0930-7249
    ISSN (online) 1439-359X
    ISSN 0939-7248 ; 0939-6764 ; 0930-7249
    DOI 10.1055/s-0043-1776976
    Database Thieme publisher's database

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    ab Jg. 2022: Lesesaal (EG)

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  4. Article ; Online: AI-augmented clinical decision in paediatric appendicitis: can an AI-generated model improve trainees' diagnostic capability?

    Shikha, Anas / Kasem, Asem / Han, Win Sabai Phyu / Wong, Janice Hui Ling

    European journal of pediatrics

    2023  Volume 183, Issue 3, Page(s) 1361–1366

    Abstract: Accurate diagnosis of paediatric appendicitis remains a challenge due to its diverse clinical presentations and reliance on subjective assessments. The integration of artificial intelligence (AI) with an expert's ''clinical sense'' has the potential to ... ...

    Abstract Accurate diagnosis of paediatric appendicitis remains a challenge due to its diverse clinical presentations and reliance on subjective assessments. The integration of artificial intelligence (AI) with an expert's ''clinical sense'' has the potential to improve diagnostic accuracy. In this study, we aimed to evaluate the effectiveness of the Artificial Intelligence Pediatric Appendicitis Decision-tree (AiPAD) model in enhancing the diagnostic capabilities of trainees and compare their performance with that of an expert supervisor. Between March 2019 and October 2022, we included paediatric patients aged 0-12 years who were referred for suspected appendicitis. Trainees collected clinical findings using five predefined parameters before ordering any imaging studies. The AiPAD model, which was blinded to the surgical team, made predictions from the supervisor's and trainees' findings independently. The diagnosis verdicts of the supervisor and the trainees were statistically evaluated in comparison to the prediction of the AI model, taking into account the revealed correct diagnosis. A total of 136 cases were included, comprising 58 cases of acute appendicitis (AA) and 78 cases of non-appendicitis (NA). The supervisor's correct verdict showed 91% accuracy compared to an average of 70% for trainees. However, if trainees were enabled with AiPAD, their accuracy would improve significantly to an average of 97%. Significantly, a strong association was observed between the expert's clinical sense and the predictions generated by AiPAD.
    Conclusion:  The utilisation of the AiPAD model in diagnosing paediatric appendicitis has significant potential to improve trainees' diagnostic accuracy, approaching the level of an expert supervisor. This hybrid approach combining AI and expert knowledge holds promise for enhancing diagnostic capabilities, reducing medical errors and improving patient outcomes.
    What is known: • Sharpening clinical judgement for pediatric appendicitis takes time and seasoned exposure. Traditional training leaves junior doctors yearning for a faster path to diagnostic mastery.
    What is new: • AI-generated models unlock the secrets of expert intuition, crafting an explicit guide for juniors to rapidly elevate their diagnostic skills. This leapfrog advancement empowers young doctors, democratizing medical expertise and paving the way for brighter outcomes in clinical training.
    MeSH term(s) Humans ; Child ; Artificial Intelligence ; Appendicitis/diagnosis ; Appendicitis/surgery ; Cognition ; Clinical Competence ; Acute Disease
    Language English
    Publishing date 2023-12-27
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 194196-3
    ISSN 1432-1076 ; 0340-6199 ; 0943-9676
    ISSN (online) 1432-1076
    ISSN 0340-6199 ; 0943-9676
    DOI 10.1007/s00431-023-05390-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Maternal awareness of breastfeeding policies in baby-friendly hospitals in Jordan.

    Kasem, Abedallah / Abuhammad, Sawsan / Alswaiti, Etab M S

    Nursing forum

    2022  Volume 57, Issue 5, Page(s) 843–850

    Abstract: Aim: This study aims to investigate the maternal perception and awareness of Baby-Friendly Hospital Initiative (BFHI) policies.: Method: A descriptive, cross-sectional research design was employed. A total of 205 mothers who gave birth in two ... ...

    Abstract Aim: This study aims to investigate the maternal perception and awareness of Baby-Friendly Hospital Initiative (BFHI) policies.
    Method: A descriptive, cross-sectional research design was employed. A total of 205 mothers who gave birth in two hospitals in Jordan comprised the sample for this study. A self-administered questionnaire developed from the review of literature and from an audit tool of one of the research settings was used to assess maternal perception of BFHI policies and maternal awareness of breastfeeding. Ethical approval was sought before data collection.
    Findings: Mothers had moderate levels of awareness of breastfeeding importance; further, most of them mentioned the provision of a policy that addresses all the steps to successful breastfeeding as a major facilitator to breastfeeding. In terms of the BFHI, mothers had a moderate level of awareness of breastfeeding initiatives and showed positive perceptions of BFHI policies.
    Conclusion and implication: Improving maternal perception of BFHI policies and maternal awareness of breastfeeding has the potential to affect breastfeeding uptake and management. Future research is recommended in the areas of (1) identification of barriers to breastfeeding among Jordan mothers, (2) determination of the impact of translating maternal awareness to breastfeeding uptake, and (3) effect of infant gender and antenatal care in breastfeeding initiation and maintenance.
    MeSH term(s) Breast Feeding ; Cross-Sectional Studies ; Female ; Health Promotion ; Hospitals ; Humans ; Jordan ; Mothers ; Policy ; Pregnancy
    Language English
    Publishing date 2022-04-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 412336-0
    ISSN 1744-6198 ; 0029-6473
    ISSN (online) 1744-6198
    ISSN 0029-6473
    DOI 10.1111/nuf.12731
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  6. Article: Acceptance of Remote Education During COVID-19 Outbreak in Undergraduate Nursing Students.

    Abuhammad, Sawsan / Gharaibeh, Besher / Kasem, Abedallah / Hamadneh, Shereen

    Nursing education perspectives

    2022  Volume 43, Issue 4, Page(s) 241–242

    Abstract: Abstract: This study aimed to examine the acceptance and predictors of remote education through Internet-based learning among undergraduate nursing students in Jordan. An online survey was used with a sample of 344 students to assess satisfaction with ... ...

    Abstract Abstract: This study aimed to examine the acceptance and predictors of remote education through Internet-based learning among undergraduate nursing students in Jordan. An online survey was used with a sample of 344 students to assess satisfaction with remote education. Responses indicated that undergraduate nursing students were unsatisfied with remote education for several reasons. Many students (n = 188, 55 percent) strongly agreed that problems and obstacles were encountered when they studied subjects electronically. The acceptance of remote education was predicted by educational level (p = .01), device used (p = .001), and Internet reliability p = .001).
    MeSH term(s) COVID-19/epidemiology ; Disease Outbreaks ; Education, Nursing, Baccalaureate ; Humans ; Reproducibility of Results ; Students, Nursing
    Language English
    Publishing date 2022-06-24
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2075410-3
    ISSN 1943-4685 ; 1536-5026
    ISSN (online) 1943-4685
    ISSN 1536-5026
    DOI 10.1097/01.NEP.0000000000000965
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 3023: Show issues Location:
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  7. Article: The Development and Validation of Artificial Intelligence Pediatric Appendicitis Decision-Tree for Children 0 to 12 Years Old

    Shikha, Anas / Kasem, Asem

    European Journal of Pediatric Surgery

    2022  Volume 33, Issue 05, Page(s) 395–402

    Abstract: Introduction: Diagnosing appendicitis in young children (0–12 years) still poses a special difficulty despite the advent of radiological investigations. Few scoring models have evolved and been applied worldwide, but with significant fluctuations in ... ...

    Abstract Introduction: Diagnosing appendicitis in young children (0–12 years) still poses a special difficulty despite the advent of radiological investigations. Few scoring models have evolved and been applied worldwide, but with significant fluctuations in accuracy upon validation.
    Aim: To utilize artificial intelligence (AI) techniques to develop and validate a diagnostic model based on clinical and laboratory parameters only (without imaging), in addition to prospective validation to confirm the findings.
    Methods: In Stage-I, observational data of children (0–12 years), referred for acute appendicitis (March 1, 2016–February 28, 2019, n  = 166), was used for model development and evaluation using 10-fold cross-validation (XV) technique to simulate a prospective validation. In Stage-II, prospective validation of the model and the XV estimates were performed (March 1, 2019–November 30, 2021, n  = 139).
    Results: The developed model, AI Pediatric Appendicitis Decision-tree (AiPAD), is both accurate and explainable, with an XV estimation of average accuracy to be 93.5% ± 5.8 (91.4% positive predictive value [PPV] and 94.8% negative predictive value [NPV]). Prospective validation revealed that the model was indeed accurate and close to the XV evaluations, with an overall accuracy of 97.1% (96.7% PPV and 97.4% NPV).
    Conclusion: The AiPAD is validated, highly accurate, easy to comprehend, and offers an invaluable tool to use in diagnosing appendicitis in children without the need for imaging. Ultimately, this would lead to significant practical benefits, improved outcomes, and reduced costs.
    Keywords AI ; clinical decision ; diagnostic model ; pediatric appendicitis ; AI decision tree ; AiPAD
    Language English
    Publishing date 2022-09-16
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article
    ZDB-ID 1065043-x
    ISSN 1439-359X ; 0939-7248 ; 0939-6764 ; 0930-7249
    ISSN (online) 1439-359X
    ISSN 0939-7248 ; 0939-6764 ; 0930-7249
    DOI 10.1055/a-1946-0157
    Database Thieme publisher's database

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3140: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: The influence of mental status on reported local urinary tract symptoms in patients with bacteraemic urinary tract infections.

    Shimoni, Zvi / Kasem, Amrani / Froom, Paul

    International journal of clinical practice

    2021  Volume 75, Issue 4, Page(s) e13741

    Abstract: Aim: In elderly patients with a urinary tract infection, the influence of mental status on the frequency of local urinary tract symptoms is uncertain. We aim to compare the frequency of reported local urinary tract symptoms between mentally intact and ... ...

    Abstract Aim: In elderly patients with a urinary tract infection, the influence of mental status on the frequency of local urinary tract symptoms is uncertain. We aim to compare the frequency of reported local urinary tract symptoms between mentally intact and cognitively impaired older people with a bacteraemic urinary tract infection.
    Methods: We retrospectively selected consecutive patients aged 65 years or older hospitalised in internal medicine departments in a regional hospital from 1 January 2015 to 31 December 2016 if they had identical bacteria isolated from blood and urine cultures. Mentally intact patients were those who were alert on admission and throughout their hospitalisation and without a prior or new diagnosis of dementia.
    Results: Of 222 patients with a bacteraemic urinary tract infection, 125 (56.3%) did not have local urinary tract symptoms, 68.8% (86/125, 95% CI-60.7%-76.9%) cognitively impaired, compared with 40.2% (39/97, 95% CI-30.4%-50.7%) in those mentally intact (P < .001).
    Conclusions: The absence of local urinary tract symptoms in elderly patients with a bacteraemic urinary tract infection is less frequent but common in those mentally intact, and should not preclude the need for a urine culture or antibiotic therapy.
    MeSH term(s) Aged ; Aged, 80 and over ; Anti-Bacterial Agents/therapeutic use ; Bacteremia/drug therapy ; Bacteremia/epidemiology ; Humans ; Retrospective Studies ; Urinary Tract Infections/drug therapy ; Urinary Tract Infections/epidemiology
    Chemical Substances Anti-Bacterial Agents
    Language English
    Publishing date 2021-02-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 1386246-7
    ISSN 1742-1241 ; 1368-5031
    ISSN (online) 1742-1241
    ISSN 1368-5031
    DOI 10.1111/ijcp.13741
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    Ua VI Zs.301: Show issues Location:
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  9. Article: Mothers' knowledge and attitudes about newborn screening in Jordan.

    Kasem, Abedallah / Razeq, Nadin M Abdel / Abuhammad, Sawsan / Alkhazali, Haneen

    Journal of community genetics

    2022  Volume 13, Issue 2, Page(s) 215–225

    Abstract: Newborn screening is an important public health program that helps save the lives of many infants worldwide. The aim of this cross-sectional descriptive study was to examine the knowledge and attitudes of mothers regarding the newborn screening test in ... ...

    Abstract Newborn screening is an important public health program that helps save the lives of many infants worldwide. The aim of this cross-sectional descriptive study was to examine the knowledge and attitudes of mothers regarding the newborn screening test in Jordan. A convenient sample of 301 mothers of newborns was interviewed to collect data, using structured questionnaires about their knowledge and attitudes regarding the newborn screening. Most mothers exhibited positive attitudes toward the newborn screening. However, their knowledge about it was only moderate; their knowledge levels contributed positively to their attitudes to the test. The mothers' source of information about the test was a significant predictor for both their level of knowledge and attitudes toward the newborn screening. The healthcare providers, particularly nurses, were identified as the main source of mothers' information in Jordan. The educative role of the health professionals is key and should be better activated to optimize the outcomes of early newborn screening. Changes in current practices regarding mothers' education about NS is recommended to increase the knowledge and enhance attitude about NS among the mothers.
    Language English
    Publishing date 2022-01-10
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2543127-4
    ISSN 1868-6001 ; 1868-310X
    ISSN (online) 1868-6001
    ISSN 1868-310X
    DOI 10.1007/s12687-021-00572-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Correction to: Mothers' knowledge and attitudes about newborn screening in Jordan.

    Kasem, Abedallah / Razeq, Nadin M Abdel / Abuhammad, Sawsan / Alkhazali, Haneen

    Journal of community genetics

    2022  Volume 13, Issue 2, Page(s) 227

    Language English
    Publishing date 2022-02-19
    Publishing country Germany
    Document type Published Erratum
    ZDB-ID 2543127-4
    ISSN 1868-6001 ; 1868-310X
    ISSN (online) 1868-6001
    ISSN 1868-310X
    DOI 10.1007/s12687-022-00583-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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