JMIR Aging - Search

View query in Help articles search

Field

e.g. mhealth

Operator

Field

Criteria

e.g. John Smith or 0000-0001-6479-5330

Exact Match for Criteria

Yes No

Search Results (1 to 7 of 7 Results)

Download search results: CSV END BibTex RIS

Sort by:

Design of a Dyadic Digital Health Module for Chronic Disease Shared Care: Development Study

Camila Benmessaoud, Kaylen J Pfisterer, Anjelica De Leon, Ashish Saragadam, Noor El-Dassouki, Karen G M Young, Raima Lohani, Ting Xiong, Quynh Pham

JMIR Hum Factors 2023;10:e45035

Download Citation: END BibTex RIS

Download PDF Download XML

An Actionable Expert-System Algorithm to Support Nurse-Led Cancer Survivorship Care: Algorithm Development Study

Kaylen J Pfisterer, Raima Lohani, Elizabeth Janes, Denise Ng, Dan Wang, Denise Bryant-Lukosius, Ricardo Rendon, Alejandro Berlin, Jacqueline Bender, Ian Brown, Andrew Feifer, Geoffrey Gotto, Shumit Saha, Joseph A Cafazzo, Quynh Pham

JMIR Cancer 2023;9:e44332

Download Citation: END BibTex RIS

Download PDF Download XML

The Complexity of Transferring Remote Monitoring and Virtual Care Technology Between Countries: Lessons From an International Workshop

Quynh Pham, David Wong, Kaylen J Pfisterer, Dionne Aleman, Nick Bansback, Joseph A Cafazzo, Alexander J Casson, Brian Chan, William Dixon, Gerasimos Kakaroumpas, Claudia Lindner, Niels Peek, Henry WW Potts, Barbara Ribeiro, Emily Seto, Charlotte Stockton-Powdrell, Alexander Thompson, Sabine van der Veer

J Med Internet Res 2023;25:e46873

Download Citation: END BibTex RIS

Download PDF Download XML

Assessing the Pragmatic Nature of Mobile Health Interventions Promoting Physical Activity: Systematic Review and Meta-analysis

Chad Stecher, Bjorn Pfisterer, Samantha M Harden, Dana Epstein, Jakob M Hirschmann, Kathrin Wunsch, Matthew P Buman

JMIR Mhealth Uhealth 2023;11:e43162

Download Citation: END BibTex RIS

Download PDF Download XML

Enhancing Food Intake Tracking in Long-term Care With Automated Food Imaging and Nutrient Intake Tracking (AFINI-T) Technology: Validation and Feasibility Assessment

An optical imaging cage was constructed to enable top-down image capture, as described in the study by Pfisterer et al [16]. The camera was connected to a computer for data acquisition, and plates were weighed at a nearby weigh station. Figure 1 shows examples of the data sets used for training the convolutional autoencoder and food classification network, which are described in detail in the following subsections.

Kaylen Pfisterer, Robert Amelard, Jennifer Boger, Heather Keller, Audrey Chung, Alexander Wong

JMIR Aging 2022;5(4):e37590

Download Citation: END BibTex RIS

Download PDF Download XML