Development of a novel automated screening method for detection of <scp>FVIII</scp> Inhibitors

Evans, Matthew; Donaldson, Keri; Eyster, M. Elaine

doi:10.1111/ijlh.12601

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…The major limitation of this study is that we could not implement our proposed pretest strategy in the actual setting of patients so far. Although simulation is widely reported upon in health care, 47 it is not clear whether the actual implementation is good or not. Moreover, the small and unitary sample source is not overwhelmingly robust for broad usage, thus large sample comparative studies are needed to validate the results.…”

Section: Discussionmentioning

confidence: 99%

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit

Luo

Kou

Feng

et al. 2021

Clin Appl Thromb Hemost

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In order to overcome the shortage of the current costly DVT diagnosis and reduce the waste of valuable healthcare resources, we proposed a new diagnostic approach based on machine learning pre-test prediction models using EHRs. We examined the sociodemographic and clinical factors in the prediction of DVT with 518 NICU admitted patients, including 189 patients who eventually developed DVT. We used cross-validation on the training data to determine the optimal parameters, and finally, the applied ROC analysis is adopted to evaluate the predictive strength of each model. Two models (GLM and SVM) with the strongest ROC were selected for DVT prediction, based on which, we optimized the current intervention and diagnostic process of DVT and examined the performance of the proposed approach through simulations. The use of machine learning based pre-test prediction models can simplify and improve the intervention and diagnostic process of patients in NICU with suspected DVT, and reduce the valuable healthcare resource occupation/usage and medical costs.

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Section: Discussionmentioning

confidence: 99%

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit

Luo

Kou

Feng

et al. 2021

Clin Appl Thromb Hemost

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Digital Technologies in Hereditary Coagulation Disorders: A Systematic Review

Kahl,

Kapsecker,

Nissen

et al. 2024

Hamostaseologie

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Background This systematic review aims to comprehensively survey digital technologies used in the prevention, diagnosis, and treatment of hereditary blood coagulation disorders. Methods The systematic review was performed according to the PRISMA guidelines. A systematic search was conducted on PubMed on January 29, 2024. Articles were excluded if they were reviews, meta-analyses, or systematic reviews. Articles were included if they were published from January 1, 2014, onward, written in English, described an actual application of digital tools, were in the context of hereditary coagulation disorders, and involved studies or trials on humans or human data with at least three subjects. Results The initial PubMed search on January 29, 2024, identified 2,843 articles, with 672 from January 1, 2014, onward. After screening, 21 articles met the exclusion and inclusion criteria. Among these, 12 focused on artificial intelligence (AI) technologies and 9 on digital applications. AI was predominantly used for diagnosis (five studies) and treatment (four studies), while digital applications were mainly used for treatment (eight studies). Most studies addressed hemophilia A, with a smaller number including hemophilia B or von Willebrand disease. Discussion The findings reveal a lack of intervention studies in the prevention, diagnosis, and treatment. However, digital tools, including AI and digital applications, are increasingly used in managing hereditary coagulation disorders. AI enhances diagnostic accuracy and personalizes treatment, while digital applications improve patient care and engagement. Despite these advancements, study biases and design limitations indicate the need for further research to fully harness the potential of these technologies.

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Development of a novel automated screening method for detection of FVIII Inhibitors

Cited by 2 publications

References 13 publications

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit

Digital Technologies in Hereditary Coagulation Disorders: A Systematic Review

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