LHSPred: A web based application for predicting lung health severity

Bhattacharjee, Sudipto; Saha, Banani; Bhattacharyya, Parthasarathi; Saha, Sudipto

doi:10.1016/j.bspc.2022.103745

Cited by 4 publications

(2 citation statements)

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“…If the tool advice is being followed or if plasma data are available, the tool will use Bayesian estimation to approximate the true pharmacokinetic profile and forecasted pharmacokinetic profile ( 67 ). A combination of regression models was utilized by LHSpred ( 78 ) to calculate the computed tomography severity score (CTSS) for COVID-19 diagnosis. The “Tool to Reduce Inappropriate Medications” (TRIM), designed to prevent polypharmacy in older adults, utilizes a rules-based algorithm to assess the medication’s appropriateness ( 68 ).…”

Section: Resultsmentioning

confidence: 99%

“…However, CDS tools will show their benefit if the diagnosis output of a particular disease is comparable to the laboratory test gold standard ( 28 ). For example, when the sensitivity and specificity between the CDS tool and laboratory standards are not significantly different ( 56 , 78 ). Approaches to validation of CDS tools in animals are an important area requiring further consideration.…”

Section: Discussionmentioning

confidence: 99%

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Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship

Yusuf,

Hillman,

Stegeman

et al. 2024

Front. Vet. Sci.

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IntroductionDigital clinical decision support (CDS) tools are of growing importance in supporting healthcare professionals in understanding complex clinical problems and arriving at decisions that improve patient outcomes. CDS tools are also increasingly used to improve antimicrobial stewardship (AMS) practices in healthcare settings. However, far fewer CDS tools are available in lowerand middle-income countries (LMICs) and in animal health settings, where their use in improving diagnostic and treatment decision-making is likely to have the greatest impact. The aim of this study was to evaluate digital CDS tools designed as a direct aid to support diagnosis and/or treatment decisionmaking, by reviewing their scope, functions, methodologies, and quality. Recommendations for the development of veterinary CDS tools in LMICs are then provided.MethodsThe review considered studies and reports published between January 2017 and October 2023 in the English language in peer-reviewed and gray literature.ResultsA total of 41 studies and reports detailing CDS tools were included in the final review, with 35 CDS tools designed for human healthcare settings and six tools for animal healthcare settings. Of the tools reviewed, the majority were deployed in high-income countries (80.5%). Support for AMS programs was a feature in 12 (29.3%) of the tools, with 10 tools in human healthcare settings. The capabilities of the CDS tools varied when reviewed against the GUIDES checklist.DiscussionWe recommend a methodological approach for the development of veterinary CDS tools in LMICs predicated on securing sufficient and sustainable funding. Employing a multidisciplinary development team is an important first step. Developing standalone CDS tools using Bayesian algorithms based on local expert knowledge will provide users with rapid and reliable access to quality guidance on diagnoses and treatments. Such tools are likely to contribute to improved disease management on farms and reduce inappropriate antimicrobial use, thus supporting AMS practices in areas of high need.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%