About: “Yes, but will it work for my patients?” Driving clinically relevant research with benchmark datasets

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About: “Yes, but will it work for my patients?” Driving clinically relevant research with benchmark datasets Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	“Yes, but will it work for my patients?” Driving clinically relevant research with benchmark datasets
Creator	Celi, Leo Keane, Pearse Lindemer, Emily Mattie, Heather Panch, Trishan Pollard, Tom
Source	Medline; PMC
abstract	Benchmark datasets have a powerful normative influence: by determining how the real world is represented in data, they define which problems will first be solved by algorithms built using the datasets and, by extension, who these algorithms will work for. It is desirable for these datasets to serve four functions: (1) enabling the creation of clinically relevant algorithms; (2) facilitating like-for-like comparison of algorithmic performance; (3) ensuring reproducibility of algorithms; (4) asserting a normative influence on the clinical domains and diversity of patients that will potentially benefit from technological advances. Without benchmark datasets that satisfy these functions, it is impossible to address two perennial concerns of clinicians experienced in computational research: “the data scientists just go where the data is rather than where the needs are,” and, “yes, but will this work for my patients?” If algorithms are to be developed and applied for the care of patients, then it is prudent for the research community to create benchmark datasets proactively, across specialties. As yet, best practice in this area has not been defined. Broadly speaking, efforts will include design of the dataset; compliance and contracting issues relating to the sharing of sensitive data; enabling access and reuse; and planning for translation of algorithms to the clinical environment. If a deliberate and systematic approach is not followed, not only will the considerable benefits of clinical algorithms fail to be realized, but the potential harms may be regressively incurred across existing gradients of social inequity.
has issue date	2020-06-19(xsd:dateTime)
bibo:doi	10.1038/s41746-020-0295-6
bibo:pmid	32577534
has license	cc-by
sha1sum (hex)	8b90f9c57fb2ce3191b511824959dec951208fbf
schema:url	https://doi.org/10.1038/s41746-020-0295-6
resource representing a document's title	“Yes, but will it work for my patients?” Driving clinically relevant research with benchmark datasets
has PubMed Central identifier	PMC7305156
has PubMed identifier	32577534
schema:publication	NPJ Digit Med
resource representing a document's body	covid:8b90f9c57fb2ce3191b511824959dec951208fbf#body_text
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