Koninklijke Philips Corporation N.V.

Mohammad Shahed Sorower

Erina Ghosh

David Paul Noren

Bryan Conroy

Eric Thomas Carlson

Srinivas Hariharan

Kailash Swaminathan

Bo Liu

Claire Yunzhu Zhao

Emma Holdrich Schwager

Daniel Craig McFarlane

Vinod Kumar

Chaitanya Kulkarni

Kristen Tgavalekos

Vikram Shivanna

Ting Feng

The present disclosure is directed to systems and methods for developing an individual-specific patient baseline for a target patient. An exemplary method involves: determining one or more acuity scores for the target patient; identifying patient health data corresponding to one or more low acuity time periods; storing retrospective clinical data from a group of patients in a second database; comparing the patient health data corresponding to the one or more low acuity time periods with retrospective clinical data from a group of patients by identifying one or more patient subgroups; determining the individual-specific patient baseline using an adaptive baseline selection algorithm, wherein the adaptive baseline selection algorithm is used to determine whether to determine the individual-specific patient baseline using patient health data or using retrospective clinical data from one or more patient subgroups; and displaying, using a user interface, the individual-specific patient baseline.

Methods and systems for patient baseline estimation

A method () for training a scoring system () comprising the steps of: (i) providing () a scoring system comprising a scoring module (); (ii) receiving () a training dataset comprising a plurality of patient data and treatment outcomes; (iii) analyzing (), using a clinical decision support algorithm, the training dataset to generate a plurality of clinical decision support recommendations; (iv) clustering (), using the scoring module, the plurality of clinical decision support recommendations into a plurality of clusters; and (v) identifying (), using the scoring module, one or more features of at least one of the plurality of clusters, and generating, based on the identified one or more features, one or more inclusion criteria for the at least one of the plurality of clusters.

Method and system for automated inclusion or exclusion criteria detection

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Natick, MA, United States of America

Mohammad Shahed Sorower